PL
 |
EN

PL EN

Preferencje help
Polish version English version Język
Widoczny [Schowaj] Abstrakt
Liczba wyników
Tytuł artykułu

Research trends on fuzzy logic controller for mobile robot navigation : a scientometric study

Autorzy
Rani Somiya , Jain Amita , Castillo Oscar
Treść / Zawartość
Pełne teksty:
rani_Research trends on fuzzy logic controller.pdf
Identyfikatory
DOI
10.14313/JAMRIS/1-2020/11
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The present study shows the scientometric analysis of the publications on the fuzzy logic controller in autonomous mobile robot navigation during the period 2000 to 2018. The data is collected using Web of Science core collection database and analyzed at various levels such as Web of Science categories, publication years, document types, funding agencies, authors, research areas, countries or region, control terms, and organization to evaluate the research patterns. An extensive study is done to find the research trends in this area.
Słowa kluczowe
EN
Wydawca
Łukasiewicz Industrial Research Institute for Automation and Measurements PIAP
Czasopismo
Journal of Automation Mobile Robotics and Intelligent Systems
Rocznik
2020
Tom
Vol. 14, No. 1
Strony
87--108
Opis fizyczny
Bibliogr. 308 poz., rys.
Twórcy
autor
Rani Somiya
  • Ambedkar Institute of Advanced Communication Technologies and Research, East Delhi, India
autor
Jain Amita
  • Ambedkar Institute of Advanced Communication Technologies and Research, East Delhi, India
autor
Castillo Oscar
ocastillo@tectijuana.mx
  • Tijuana Institute of Technology, B.C., Tijuana, México
Bibliografia
  • [1] H. A. Hagras, “A Hierarchical Type-2 Fuzzy Logic Control Architecture for Autonomous Mobile Robots”, IEEE Transactions on Fuzzy Systems, vol. 12, no. 4, 2004, 524–539, DOI: 10.1109/TFUZZ.2004.832538.
  • [2] R. Martínez, O. Castillo and L. T. Aguilar, “Optimization of interval type-2 fuzzy logic controllers for a perturbed autonomous wheeled mobile robot using genetic algorithms”, Information Sciences, vol. 179, no. 13, 2009, 2158–2174, DOI: 10.1016/j.ins.2008.12.028.
  • [3] M. A. P. Garcia, O. Montiel, O. Castillo, R. Sepúlveda and P. Melin, “Path planning for autonomous mobile robot navigation with ant colony optimization and fuzzy cost function evaluation”, pplied Soft Computing, vol. 9, no. 3, 2009, 1102–1110, DOI: 10.1016/j.asoc.2009.02.014.
  • [4] H. Seraji and A. Howard, “Behavior-based robot navigation on challenging terrain: A fuzzy logic approach”, IEEE Transactions on Robotics and Automation, vol. 18, no. 3, 2002, 308–321, DOI: 10.1109/TRA.2002.1019461.
  • [5] G. Antonelli, S. Chiaverini and G. Fusco, “A Fuzzy-Logic-Based Approach for Mobile Robot Path Tracking”, IEEE Transactions on Fuzzy Systems, vol. 15, no. 2, 2007, 211–221, DOI: 10.1109/TFUZZ.2006.879998.
  • [6] P. Rusu, E. M. Petriu, T. E. Whalen, A. Cornell and H. J. W. Spoelder, “Behavior-based neuro-fuzzy controller for mobile robot navigation”, IEEE Transactions on Instrumentation and Measurement, vol. 52, no. 4, 2003, 1335–1340, DOI: 10.1109/TIM.2003.816846.
  • [7] J. L. Martínez, A. Mandow, J. Morales, S. Pedrazaand A. García-Cerezo, “Approximating Kinematics for Tracked Mobile Robots”, The International Journal of Robotics Research, vol. 24, o. 10, 2005, 867–878, DOI: 10.1177/0278364905058239.
  • [8] C.-F. Juang and Y.-C. Chang, “EvolutionaryGroup-Based Particle-Swarm-Optimized Fuzzy Controller With Application to Mobile-Robot Navigation in Unknown Environments”, IEEE Transactions on Fuzzy Systems, vol. 19, no. 2, 2011, 379–392, DOI: 10.1109/TFUZZ.2011.2104364.
  • [9] C. Ye, N. H. C. Yung and D.-W. Wang, “A fuzzy controller with supervised learning assisted reinforcement learning algorithm for obstacle avoidance”, IEEE Transactions on Systems, Man and Cybernetics, Part B (Cybernetics), vol. 33, o. 1, 2003, 17–27, DOI: 10.1109/TSMCB.2003.808179.
  • [10] S. Sanchez-Solano, A. J. Cabrera, I. Baturone, F. J. Moreno-Velo and M. Brox, “FPGA Implementation of Embedded Fuzzy Controllers for Robotic Applications”, IEEE Transactions on Industrial Electronics, vol. 54, no. 4, 2007, 1937–1945, DOI: 10.1109/TIE.2007.898292.
  • [11] O. Montiel, U. Orozco-Rosas and R. Sepúlveda, “Path planning for mobile robots using Bacterial Potential Field for avoiding static and dynamic obstacles”, Expert Systems with Applications, vol. 42, no. 12, 2015, 5177–5191, DOI: 10.1016/j.eswa.2015.02.033.
  • [12] W. Gueaieb and M. S. Miah, “An Intelligent Mobile Robot Navigation Technique Using RFID Technology”, IEEE Transactions on Instrumentation and Measurement, vol. 57, no. 9, 2008, 1908–1917, DOI: 10.1109/TIM.2008.919902.
  • [13] F. Abdessemed, K. Benmahammed and E. Monacelli, “A fuzzy-based reactive controller for a non-holonomic mobile robot”, Robotics and Autonomous Systems, vol. 47, no. 1, 2004, 31–46, DOI: 10.1016/j.robot.2004.02.006.
  • [14] N. C. Tsourveloudis, K. P. Valavanis and T. Hebert, “Autonomous vehicle navigation utilizing electrostatic potential fields and fuzzy logic”, IEEE Transactions on Robotics and Automation, vol. 17, no. 4, 2001, 490–497, DOI: 10.1109/70.954761.
  • [15] H. Maaref and C. Barret, “Sensor-based navigation of a mobile robot in an indoor environment”, Robotics and Autonomous Systems, vol. 38, no. 1, 2002, 2020–01-18, DOI: 10.1016/S0921-8890(01)00165-8.
  • [16] S. K. Pradhan, D. R. Parhi and A. K. Panda, “Fuzzy logic techniques for navigation of several mobile robots”, Applied Soft Computing, vol. 9, no. 1, 2009, 290–304, DOI: 10.1016/j.asoc.2008.04.008.
  • [17] M. Wang and J. N. K. Liu, “Fuzzy logic-based real-time robot navigation in unknown environment with dead ends”, Robotics and Autonomous Systems, vol. 56, no. 7, 2008, 625–643, DOI: 10.1016/j.robot.2007.10.002.
  • [18] C.-H. Hsu and C.-F. Juang, “Evolutionary Robot Wall-Following Control Using Type-2 Fuzzy Controller With Species-DE-Activated Continuous ACO”, IEEE Transactions on Fuzzy Systems, vol. 21, no. 1, 2013, 100–112, DOI: 10.1109/TFUZZ.2012.2202665.
  • [19] S.-M. Lee, K.-Y. Kwon and J. Joh, “A fuzzy logic for autonomous navigation of marine vehicles satisfying COLREG guidelines”, International Journal of Control Automation and Systems, vol. 2, no. 2, 2004, 171-181.
  • [20] X. Yang, M. Moallem and R. V. Patel, “A Layered Goal-Oriented Fuzzy Motion Planning Strategy for Mobile Robot Navigation”, IEEE Transactions on Systems, Man and Cybernetics, Part B (Cybernetics), vol. 35, no. 6, 2005, 1214–1224, DOI: 10.1109/TSMCB.2005.850177.
  • [21] E. Aguirre and A. González, “Fuzzy behaviors for mobile robot navigation: design, coordination and fusion”, International Journal of Approximate Reasoning, vol. 25, no. 3, 2000, 255–289, DOI: 10.1016/S0888-613X(00)00056-6.
  • [22] C.-J. Kim and D. Chwa, “Obstacle Avoidance Method for Wheeled Mobile Robots Using Interval Type-2 Fuzzy Neural Network”, IEEE Transactions on Fuzzy Systems, vol. 23, no. 3, 2015, 677–687, DOI: 10.1109/TFUZZ.2014.2321771.
  • [23] K. R. S. Kodagoda, W. S. Wijesoma and E.K. Teoh, “Fuzzy speed and steering control of an AGV”, IEEE Transactions on Control Systems Technology, vol. 10, no. 1, 2002, 112–120, DOI: 10.1109/87.974344.
  • [24] S. Kim and J.-H. Kim, “Adaptive fuzzy-networkbased C-measure map-matching algorithm for car navigation system”, IEEE Transactions on Industrial Electronics, vol. 48, no. 2, 2001, 432–441, DOI: 10.1109/41.915423.
  • [25] N. B. Hui, V. Mahendar and D. K. Pratihar, “Timeoptimal, collision-free navigation of a car-like mobile robot using neuro-fuzzy approaches”, Fuzzy Sets and Systems, vol. 157, no. 16, 2006, 2171–2204, DOI: 10.1016/j.fss.2006.04.004.
  • [26] M. F. Selekwa, D. D. Dunlap, D. Shi and E. G. Collins, “Robot navigation in very cluttered environments by preference-based fuzzy behaviors”, Robotics and Autonomous Systems, vol. 56, no. 3, 2008, 231–246, DOI: 10.1016/j.robot.2007.07.006.
  • [27] H. Mousazadeh, “A technical review on navigation systems of agricultural autonomous ff-road vehicles”, Journal of Terramechanics, vol. 50, no. 3, 2013, 211–232, DOI: 10.1016/j.jterra.2013.03.004.
  • [28] M. Mucientes and J. Casillas, “Quick Design of Fuzzy Controllers With Good Interpretability in Mobile Robotics”, IEEE Transactions on Fuzzy Systems, vol. 15, no. 4, 2007, 636–651, DOI: 10.1109/TFUZZ.2006.889889.
  • [29] J. L. Martínez, J. González, J. Morales, A. Mandow and A. J. García-Cerezo, “Mobile robot motion estimation by 2D scan matching with genetic and iterative closest point algorithms”, Journal of Field Robotics, vol. 23, no. 1, 2006, 21–34, DOI: 10.1002/rob.20104.
  • [30] J. Xue, L. Zhang and T. E. Grift, “Variable field-ofview machine vision based row guidance of an agricultural robot”, Computers and Electronics in Agriculture, vol. 84, 2012, 85–91, DOI: 10.1016/j.compag.2012.02.009.
  • [31] R.-J. Wai and Y.-W. Lin, “Adaptive Moving-Target Tracking Control of a Vision-Based Mobile Robot via a Dynamic Petri Recurrent Fuzzy Neural Network”, IEEE Transactions on Fuzzy Systems, vol. 21, no. 4, 2013, 688–701, DOI: 10.1109/TFUZZ.2012.2227974.
  • [32] F. Cupertino, V. Giordano, D. Naso and L. Delfine, “Fuzzy control of a mobile robot”, IEEE Robotics & Automation Magazine, vol. 13, no. 4, 2006, 74–81, DOI: 10.1109/MRA.2006.250563.
  • [33] L. Moreno, J. M. Armingol, S. Garrido, A. de la Escalera and M. A. Salichs, “A Genetic Algorithm for Mobile Robot Localization Using Ultrasonic Sensors”, Journal of Intelligent and Robotic Systems, vol. 34, no. 2, 2002, 135–154, DOI: 10.1023/A:1015664517164.
  • [34] F. Arambula Cosío and M. A. Padilla Castañeda, “Autonomous robot navigation using adaptive potential fields”, Mathematical and Computer Modelling, vol. 40, no. 9-10, 2004, 1141–1156, DOI: 10.1016/j.mcm.2004.05.001.
  • [35] R. Kala, A. Shukla and R. Tiwari, “Fusion of probabilistic A* algorithm and fuzzy inferencel system for robotic path planning”, Artificial Intelligence Review, vol. 33, no. 4, 2010, 307–327, DOI: 10.1007/s10462-010-9157-y.
  • [36] E. Kayacan, E. Kayacan, H. Ramon, O. Kaynak and W. Saeys, “Towards Agrobots: TrajectoryControl of an Autonomous Tractor Using Type2 Fuzzy Logic Controllers”, IEEE/ASME Transactions on Mechatronics, vol. 20, no. 1, 2015, 287–298, DOI: 10.1109/TMECH.2013.2291874.
  • [37] C.-H. Hsu and C.-F. Juang, “Multi-Objective Continuous-Ant-Colony-Optimized FC for Robot Wall-Following Control”, IEEE Computational Intelligence Magazine, vol. 8, no. 3, 2013, 28–40, DOI: 10.1109/MCI.2013.2264233.
  • [38] D. R. Parhi, “Navigation of Mobile Robots Using a Fuzzy Logic Controller”, Journal of Intelligent and Robotic Systems, vol. 42, no. 3, 2005, 253–273, DOI: 10.1007/s10846-004-7195-x.
  • [39] M. Faisal, R. Hedjar, M. Al Sulaiman and K. AlMutib, “Fuzzy Logic Navigation and Obstacle Avoidance by a Mobile Robot in an Unknown Dynamic Environment”, International Journal of Advanced Robotic Systems, vol. 10, no. 1, 2013, DOI: 10.5772/54427.
  • [40] C.-C. Tsai, H.-C. Huang and S.-C. Lin, “FPGABased Parallel DNA Algorithm for Optimal Configurations of an Omnidirectional Mobile Service Robot Performing Fire Extinguishment”, IEEE Transactions on Industrial Electronics, vol. 58, no. 3, 2011, 1016–1026, DOI: 10.1109/TIE.2010.2048291.
  • [41] H.-H. Lin, C.-C. Tsai and J.-C. Hsu, “Ultrasonic Localization and Pose Tracking of an Autonomous Mobile Robot via Fuzzy Adaptive Extended Information Filtering”, IEEE Transactions on Instrumentation and Measurement, vol. 57, no. 9, 2008, 2024–2034, DOI: 10.1109/TIM.2008.919020.
  • [42] H. Li and S. X. Yang, “A behavior-based mobile robot with a visual landmark-recognition system”, IEEE/ASME Transactions on Mechatronics, vol. 8, no. 3, 2003, 390–400, DOI: 10.1109/TMECH.2003.816818.
  • [43] J. B. Mbede, X.-H. Huang and M. Wang, “Robust neuro-fuzzy sensor-based motion control among dynamic obstacles for robot manipulators”, IEEE Transactions on Fuzzy Systems, vol. 11, no. 2, 2003, 249–261, DOI: 10.1109/TFUZZ.2003.809906.
  • [44] T. Haferlach, J. Wessnitzer, M. Mangan and B. Webb, “Evolving a Neural Model of Insect Path Integration”, Adaptive Behavior, vol. 15, no. 3, 2007, 273–287, DOI: 10.1177/1059712307082080.
  • [45] R. Huq, G. K. I. Mann and R. G. Gosine, “Behaviormodulation technique in mobile robotics using fuzzy discrete event system”, IEEE Transactions on Robotics, vol. 22, no. 5, 2006, 903–916, DOI: 10.1109/TRO.2006.878937.
  • [46] H. Mehrjerdi, M. Saad and J. Ghommam, “Hierarchical Fuzzy Cooperative Control and Path Following for a Team of Mobile Robots”, IEEE/ASME Transactions on Mechatronics, vol. 16, no. 5, 2011, 907–917, DOI: 10.1109/TMECH.2010.2054101.
  • [47] J. Velagic, B. Lacevic and B. Perunicic, “A 3-level autonomous mobile robot navigation system designed by using reasoning/search approaches”, Robotics and Autonomous Systems, vol. 54, no. 12, 2006, 989–1004, DOI: 10.1016/j.robot.2006.05.006.
  • [48] H. Hagras, V. Callaghan and M. Colley, “Learning and adaptation of an intelligent mobile robotnavigator operating in unstructured environment based on a novel online Fuzzy–Genetic system”, Fuzzy Sets and Systems, vol. 141, no. 1, 2004, 107–160, DOI: 10.1016/S0165-0114(03)00116-7.
  • [49] D. K. Pratihar, K. Deb and A. Ghosh, “Optimal path and gait generations simultaneously of a six-legged robot using a GA-fuzzy approach”, Robotics and Autonomous Systems, vol. 41, no. 1, 2002, 2020–01-20, DOI: 10.1016/S0921-8890(02)00273-7.
  • [50] J. K. Pothal and D. R. Parhi, “Navigation of multiple mobile robots in a highly clutter terrains using adaptive neuro-fuzzy inference system”, Robotics and Autonomous Systems, vol. 72, 2015, 48–58, DOI: 10.1016/j.robot.2015.04.007.
  • [51] D. Gu and H. Hu, “Using Fuzzy Logic to Design Separation Function in Flocking Algorithms”, IEEE Transactions on Fuzzy Systems, vol. 16, no. 4, 2008, 826–838, DOI: 10.1109/TFUZZ.2008.917289.
  • [52] A. Bakdi, A. Hentout, H. Boutami, A. Maoudj, O. Hachour and B. Bouzouia, “Optimal path lanning and execution for mobile robots using genetic algorithm and adaptive fuzzy-logic control”, Robotics and Autonomous Systems, vol. 89, 2017, 95–109, DOI: 10.1016/j.robot.2016.12.008.
  • [53] K. Samsudin, F. A. Ahmad and S. Mashohor, “A highly interpretable fuzzy rule base using ordinal structure for obstacle avoidance of mobile robot”, Applied Soft Computing, vol. 11, no. 2, 2011, 1631–1637, DOI: 10.1016/j.asoc.2010.05.002.
  • [54] S. X. Yang, H. Li, M. Q. H. Meng and P. X. Liu, “An Embedded Fuzzy Controller for a BehaviorBased Mobile Robot With Guaranteed Performance”, IEEE Transactions on Fuzzy Systems, vol. 12, no. 4, 2004, 436–446, DOI: 10.1109/TFUZZ.2004.832524.
  • [55] M. Akbarzadeh, K. Kumbla, E. Tunstel and M. Jamshidi, “Soft computing for autonomous robotic systems”, Computers & Electrical Engineering, vol. 26, no. 1, 2000, 5–32, DOI: 10.1016/S0045-7906(99)00027-0.
  • [56] H. Miao and Y.-C. Tian, “Dynamic robot path planning using an enhanced simulated annealing approach”, Applied Mathematics and Computation, vol. 222, 2013, 420–437, DOI: 10.1016/j.amc.2013.07.022.
  • [57] R. Chatterjee and F. Matsuno, “Use of single side reflex for autonomous navigation of mobile robots in unknown environments”, Robotics and Autonomous Systems, vol. 35, no. 2, 2001, 77–96, DOI: 10.1016/S0921-8890(00)00124-X.
  • [58] K. Althoefer, B. Krekelberg, D. Husmeier and L. Seneviratne, “Reinforcement learning in a rule-based navigator for robotic manipulators”, Neurocomputing, vol. 37, 2001, 51–70, DOI: 10.1016/S0925-2312(00)00307-6.[59] J. C. Mohanta, D. R. Parhi and S. K. Patel, “Path planning strategy for autonomous mobile robot navigation using Petri-GA optimisation”, Computers & Electrical Engineering, vol. 37, no. 6, 2011, 1058–1070, DOI: 10.1016/j.compeleceng.2011.07.007.
  • [60] J. Mbede, P. Ele, C. Mvehabia, Y. Toure, V. Graefe and S. Ma, “Intelligent mobile manipulator navigation using adaptive neuro-fuzzy systems”, Information Sciences, vol. 171, no. 4, 2005, 447–474, DOI: 10.1016/j.ins.2004.09.014.
  • [61] J. Z. Sasiadek and Q. Wang, “Low cost automation using INS/GPS data fusion for accurate positioning”, Robotica, vol. 21, no. 3, 2003, 255–260, DOI: 10.1017/S0263574702004757.
  • [62] M. Al-Khatib and J. J. Saade,“An efficient datadriven fuzzy approach to the motion planning problem of a mobile robot”, Fuzzy Sets and Systems, vol. 134, no. 1, 2003, 65–82, DOI: 10.1016/S0165-0114(02)00230-0.
  • [63] F. Hoffmann, D. Schauten and S. Holemann, “Incremental Evolutionary Design of TSK Fuzzy Controllers”, IEEE Transactions on Fuzzy Systems, vol. 15, no. 4, 2007, 563–577, DOI: 10.1109/TFUZZ.2007.900905.
  • [64] V. Kanakakis, K. P. Valavanis and N. C. Tsourveloudis, “Fuzzy-Logic Based Navigation of Underwater Vehicles”, Journal of Intelligent and Robotic Systems, vol. 40, no. 1, 2004, 45–88, DOI: 10.1023/B:JINT.0000034340.87020.05.
  • [65] M. Algabri, H. Mathkour, H. Ramdane and M. Alsulaiman, “Comparative study of soft computing techniques for mobile robot navigation in an unknown environment”, Computers in Human Behavior, vol. 50, 2015, 42–56, DOI: 10.1016/j.chb.2015.03.062.
  • [66] K. Das Sharma, A. Chatterjee and A. Rakshit, “A PSO–Lyapunov Hybrid Stable Adaptive uzzy Tracking Control Approach for VisionBased Robot Navigation”, IEEE Transactions on Instrumentation and Measurement, vol. 61, no. 7, 2012, 1908–1914, DOI: 10.1109/TIM.2012.2182868.
  • [67] K. Madhava Krishna and P. K. Kalra, “Detection, Tracking and Avoidance of Multiple Dynamic Objects”, Journal of Intelligent and Robotic Systems, vol. 33, no. 4, 2002, 371–408, DOI: 10.1023/A:1015508906105.
  • [68] J. Rosenblatt, S. Williams and H. DurrantWhyte, “A behavior-based architecture for autonomous underwater exploration”, Information Sciences, vol. 145, no. 2020-01-02, 2002, 69–87, DOI: 10.1016/S0020-0255(02)00224-4.
  • [69] J. B. Mbede, X. Huang and M. Wang, “Fuzzy motion planning among dynamic obstacles using artificial potential fields for robot manipulators”, Robotics and Autonomous Systems, vol. 32, no. 1, 2000, 61–72, DOI: 10.1016/S0921-8890(00)00073-7.
  • [70] H.-M. Feng, C.-Y. Chen and J.-H. Horng, “Intelligent omni-directional vision-based mobile robot fuzzy systems design and implementation”, Expert Systems with Applications, vol. 37, no. 5, 2010, 4009–4019, DOI: 10.1016/j.eswa.2009.11.030.
  • [71] E. A. Merchan-Cruz and A. S. Morris, “FuzzyGA-based trajectory planner for robot manipulators sharing a common workspace”, IEEE Transactions on Robotics, vol. 22, no. 4, 2006, 613–624, DOI: 10.1109/TRO.2006.878789.
  • [72] X.-D. Chen, K. Watanabe, K. Kiguchi and K. Izumi, “An ART-based fuzzy controller for the adaptive navigation of a quadruped robot”, IEEE/ASME Transactions on Mechatronics, vol. 7, no. 3, 2002, 318–328, DOI: 10.1109/TMECH.2002.802722.
  • [73] C.-F. Juang, T.-L. Jeng and Y.-C. Chang, “An Interpretable Fuzzy System Learned Through Online Rule Generation and Multiobjective ACO With a Mobile Robot Control Application”, IEEE Transactions on Cybernetics, vol. 46, no. 12, 2016, 2706–2718,DOI: 10.1109/TCYB.2015.2486779.
  • [74] A. H. Karami and M. Hasanzadeh, “An adaptive genetic algorithm for robot motion planning in 2D complex environments”, Computers & Electrical Engineering, vol. 43, 2015, 317–329, DOI: 10.1016/j.compeleceng.2014.12.014.
  • [75] N. B. Hui and D. K. Pratihar, “A comparative study on some navigation schemes of a real robot tackling moving obstacles”, Robotics and Computer-Integrated Manufacturing, vol. 25, no. 4-5, 2009, 810–828, DOI: 10.1016/j.rcim.2008.12.003.
  • [76] S. Nefti, M. Oussalah, K. Djouani and J. Pontnau, “Intelligent Adaptive Mobile Robot Navigation”, Journal of Intelligent and Robotic Systems, vol. 30, no. 4, 2001, 311–329, DOI: 10.1023/A:1011190306492.
  • [77] P. K. Mohanty and D. R. Parhi, “A New Intelligent Motion Planning for Mobile Robot Navigation using Multiple Adaptive Neuro-Fuzzy Inference System”, Applied Mathematics & Information Sciences, vol. 8, no. 5, 2014, 2527–2535,DOI: 10.12785/amis/080551.
  • [78] D. R. Parhi and J. C. Mohanta, “Navigational control of several mobile robotic agents using Petri-potential-fuzzy hybrid controller”, Applied Soft Computing, vol. 11, no. 4, 2011, 3546–3557, DOI: 10.1016/j.asoc.2011.01.027.
  • [79] E. Tunstel, M. A. A. de Oliveira and S. Berman, “Fuzzy behavior hierarchies for multi-robot control”, International Journal of Intelligent Systems, vol. 17, no. 5, 2002, 449–470, DOI: 10.1002/int.10032.
  • [80] N. Kubota, T. Morioka, F. Kojima and T. Fukuda, “Learning of mobile robots using perceptionbased genetic algorithm”, Measurement, vol. 29, no. 3, 2001, 237–248, DOI: 10.1016/S0263-2241(00)00044-0.
  • [81] D. Dong, C. Chen, C. Zhang and Z. Chen, “Quantum robot: structure, algorithms and applications”, Robotica, vol. 24, no. 4, 2006, 513–521, DOI: 10.1017/S0263574705002596.
  • [82] H. Yavuz and A. Bradshaw, “A New Conceptual Approach to the Design of Hybrid Control Architecture for Autonomous Mobile Robots”, Journal of Intelligent and Robotic Systems, vol. 34, no. 1, 2002, 2020–01-26, DOI: 10.1023/A:1015522622034.
  • [83] H. Maaref and C. Barret, “Sensor-based fuzzy navigation of an autonomous mobile robot in an indoor environment”, Control Engineering ractice, vol. 8, no. 7, 2000, 757–768, DOI: 10.1016/S0967-0661(99)00200-2.
  • [84] Y. Li, G. Wang, H. Chen, L. Shi and L. Qin, “An Ant Colony Optimization Based Dimension Reduction Method for High-Dimensional Datasets”, Journal of Bionic Engineering, vol. 10, no. 2, 2013, 231–241, DOI: 10.1016/S1672-6529(13)60219-X.
  • [85] T. Yang and V. Aitken, “Evidential Mapping for Mobile Robots With Range Sensors”, IEEE Transactions on Instrumentation and Measurement, vol. 55, no. 4, 2006, 1422–1429, DOI: 10.1109/TIM.2006.876399.
  • [86] P. K. Mohanty and D. R. Parhi, “A new hybrid optimization algorithm for multiple mobile robots navigation based on the CS-ANFIS approach”, Memetic Computing, vol. 7, no. 4, 2015, 55–273, DOI: 10.1007/s12293-015-0160-3.
  • [87] G. K. Venayagamoorthy, L. L. Grant and S. Doctor, “Collective robotic search using hybrid techniques: Fuzzy logic and swarm intelligence inspired by nature”, Engineering Applications of Artificial Intelligence, vol. 22, no. 3, 2009, 431–441, DOI: 10.1016/j.engappai.2008.10.002.
  • [88] E. Aguirre and A. González, “A Fuzzy Perceptual Model for Ultrasound Sensors Applied to Intelligent Navigation of Mobile Robots”, Applied Intelligence, vol. 19, no. 3, 2003, 171–187, DOI: 10.1023/A:1026057906312.
  • [89] A. Pandey and D. R. Parhi, “Optimum path planning of mobile robot in unknown static and dynamic environments using Fuzzy-Wind Driven Optimization algorithm”, Defence Technology, vol. 13, no. 1, 2017, 47–58, DOI: 10.1016/j.dt.2017.01.001.
  • [90] M. S. Masmoudi, N. Krichen, M. Masmoudi and N. Derbel, “Fuzzy logic controllers design for omnidirectional mobile robot navigation”, Applied Soft Computing, vol. 49, 2016, 901–919, DOI: 10.1016/j.asoc.2016.08.057.
  • [91] S.-Y. Lee and H.-W. Yang, “Navigation of automated guided vehicles using magnet spot guidance method”, Robotics and ComputerIntegrated Manufacturing, vol. 28, no. 3, 2012, 425–436, DOI: 10.1016/j.rcim.2011.11.005.
  • [92] A. Jayasiri, G. K. I. Mann and R. G. Gosine, “Behavior Coordination of Mobile Robotics Using Supervisory Control of Fuzzy Discrete Event Systems”, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics), vol. 41, no. 5, 2011, 1224–1238, DOI: 10.1109/TSMCB.2011.2119311.
  • [93] A. M. Martinez and J. Vitria, “Clustering in image space for place recognition and visual annotations for human-robot interaction”, IEEE Transactions on Systems, Man and Cybernetics, Part B (Cybernetics), vol. 31, no. 5, 2001, 669–682, DOI: 10.1109/3477.956029.
  • [94] W. L. Xu, “A virtual target approach for resolving the limit cycle problem in navigation of fuzzy behaviour-based mobile robot”, Robotics and Autonomous Systems, vol. 30, no. 4, 2000, 315–324, DOI: 10.1016/S0921-8890(99)00099-8.
  • [95] C.-F. Juang, M.-G. Lai and W.-T. Zeng, “Evolutionary Fuzzy Control and Navigation for Two Wheeled Robots Cooperatively Carrying an Object in Unknown Environments”, IEEE Transactions on Cybernetics, vol. 45, no. 9, 2015, 1731–1743, DOI: 10.1109/TCYB.2014.2359966.
  • [96] F. Janabi-Sharifi and I. Hassanzadeh, “Experimental Analysis of Mobile-Robot Teleoperation via Shared Impedance Control”, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics), vol. 41, no. 2, 2011, 591–606, DOI: 10.1109/TSMCB.2010.2073702.
  • [97] S. Nefti, M. Oussalah and U. Kaymak, “A New Fuzzy Set Merging Technique Using InclusionBased Fuzzy Clustering”, IEEE Transactions on Fuzzy Systems, vol. 16, no. 1, 2008, 145–161, DOI: 10.1109/TFUZZ.2007.902011.
  • [98] K.-Y. Tu and J. Baltes, “Fuzzy potential Energy for a map approach to robot navigation”, Robotics and Autonomous Systems, vol. 54, no. 7, 2006, 574–589, DOI: 10.1016/j.robot.2006.04.001.
  • [99] J. Huang, M. Ri, D. Wu and S. Ri,“Interval Type-2 Fuzzy Logic Modeling and Control of a Mobile Two-Wheeled Inverted Pendulum”, IEEE Transactions on Fuzzy Systems, vol. 26, no. 4, 2018, 2030–2038, DOI: 10.1109/TFUZZ.2017.2760283.
  • [100] U. Orozco-Rosas, O. Montiel and R. Sepúlveda, “Pseudo-Bacterial Potential Field Based Path Planner for Autonomous Mobile Robot Navigation”, International Journal of Advanced Robotic Systems, vol. 12, no. 7, 2015, DOI: 10.5772/60715.
  • [101] J. M. Alonso, M. Ocaña, N. Hernandez, F. Herranz, A. Llamazares, M. A. Sotelo, L. M. Bergasa and L. Magdalena, “Enhanced WiFi localization system based on Soft Computing techniques to deal with small-scale variations in wireless sensors”, Applied Soft Computing, vol. 11, no. 8, 011, 4677–4691, DOI: 10.1016/j.asoc.2011.07.015.
  • [102] Y.-D. Hong, Y.-H. Kim, J.-H. Han, J.-K. Yoo and .-H. Kim, “Evolutionary Multiobjective Footstep Planning for Humanoid Robots”, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews), vol. 41, no. 4, 2011, 520–532, DOI: 10.1109/TSMCC.2010.2063700.
  • [103] R. Kala, A. Shukla and R. Tiwari, “Robotic path planning using evolutionary momentumbased exploration”, Journal of Experimental & Theoretical Artificial Intelligence, vol. 23, no. 4, 2011, 469–495, DOI: 10.1080/0952813X.2010.490963.
  • [104] H. Boubertakh, M. Tadjine and P. Glorennec, “A new mobile robot navigation method using fuzzy logic and a modified Q-learning algorithm”, Journal of Intelligent & Fuzzy Systems, vol. 21, no. 1-2, 2010, 113–119, DOI: 10.3233/IFS-2010-0440.
  • [105] M. Mucientes, R. Iglesias, C. V. Regueiro, A.Bugarin, P. Carinena and S. Barro, “Fuzzy temporal rules for mobile robot guidance in dynamic environments”, IEEE Transactions on Systems, Man and Cybernetics, Part C (Applications and Reviews), vol. 31, no. 3, 2001, 391–398, DOI: 10.1109/5326.971667.
  • [106] O. Montiel-Ross, R. Sepúlveda, O. Castillo and P. Melin, “Ant colony test center for planning autonomous mobile robot navigation”, Computer Applications in Engineering Education, vol. 21, no. 2, 2013, 214–229, DOI: 10.1002/cae.20463.
  • [107] S. Hong and S. Park, “Minimal-Drift Heading Measurement using a MEMS Gyro for Indoor Mobile Robots”, Sensors, vol. 8, no. 11, 2008, 7287–7299, DOI: 10.3390/s8117287.
  • [108] G.-C. Luh and W.-W. Liu, “Motion planning for mobile robots in dynamic environments using a potential field immune network”, Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering, vol. 221, no. 7, 2007, 1033–1045, DOI: 10.1243/09596518JSCE400.
  • [109] M. Mitić and Z. Miljković, “Bio-inspired approach to learning robot motion trajectories and visual control commands”, Expert Systems with Applications, vol. 42, no. 5, 2015, 2624–2637, DOI: 10.1016/j.eswa.2014.10.053.
  • [110] R. Huq, G. K. I. Mann and R. G. Gosine, “Distributed fuzzy discrete event system for robotic sensory information processing”, Expert Systems, vol. 23, no. 5, 2006, 273–289, DOI: 10.1111/j.1468-0394.2006.00409.x.
  • [111] P.-S. Tsai, L.-S. Wang and F.-R. Chang, “Modeling and hierarchical tracking control of triwheeled mobile robots”, IEEE Transactions on Robotics, vol. 22, no. 5, 2006, 1055–1062, DOI: 10.1109/TRO.2006.878964.
  • [112] B. Sun, D. Zhu, L. Jiang and S. X. Yang, “A novel fuzzy control algorithm for three-dimensional AUV path planning based on sonar model”, Journal of Intelligent & Fuzzy Systems, vol. 26, no. 6, 2014, 2913–2926, DOI: 10.3233/IFS-130957.
  • [113] L. Khriji, F. Touati, K. Benhmed and A. Al-Yahmedi, “Mobile Robot Navigation Based on Q-Learning Technique”, International Journal of Advanced Robotic Systems, vol. 8, no. 1, 2011, DOI: 10.5772/10528.
  • [114] H. M. Barberá and A. G. Skarmeta, “A framework for defining and learning fuzzy behaviors for autonomous mobile robots”, International Journal of Intelligent Systems, vol. 17, no. 1, 2002, DOI: 10.1002/int.1000.
  • [115] J. Bengochea-Guevara, J. Conesa-Muñoz, D. Andújar and A. Ribeiro, “Merge Fuzzy Visual Servoing and GPS-Based Planning to Obtain a Proper Navigation Behavior for a Small CropInspection Robot”, Sensors, vol. 16, no. 3, 2016, DOI: 10.3390/s16030276.
  • [116] C.-H. Kuo, H.-C. Chou and S.-Y. Tasi, “Pneumatic Sensor: A Complete Coverage Improvement Approach for Robotic Cleaners”, IEEE Transactions on Instrumentation and Measurement, vol. 60, no. 4, 2011, 1237–1256, DOI: 10.1109/TIM.2010.2101312.
  • [117] J. Kim, Y.-G. Kim and J. An, “A Fuzzy Obstacle Avoidance Controller Using a Lookup-Table Sharing Method and Its Applications for Mobile Robots”, International Journal of Advanced Robotic Systems, vol. 8, no. 5, 2011, DOI: 10.5772/45700.
  • [118] D. Herrero-Pérez, H. Martínez-Barberá, K. LeBlanc and A. Saffiotti, “Fuzzy uncertainty modeling for grid based localization of mobile robots”, International Journal of Approximate Reasoning, vol. 51, no. 8, 2010, 912–932, DOI: 10.1016/j.ijar.2010.06.001.
  • [119] M. Yahyaei, J. E. Jam and R. Hosnavi, “Controlling the navigation of automatic guided vehicle (AGV) using integrated fuzzy logic controller with programmable logic controller (IFLPLC)—stage 1”, The International Journal of Advanced Manufacturing Technology, vol. 47, no. 5-8, 2010, 795–807, DOI: 10.1007/s00170-009-2017-8.
  • [120] R. Abiyev, D. Ibrahim and B. Erin, “EDURobot: an educational computer simulation program for navigation of mobile robots in the presence of obstacles”, The International journal of engineering education, vol. 26, no. 1, 2010, 18–29.
  • [121] D. R. Parhi and M. K. Singh, “Intelligent fuzzy interface technique for the control of an autonomous mobile robot”, Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, vol. 222, no. 11, 2008, 2281–2292, DOI: 10.1243/09544062JMES955.
  • [122] R. Munoz-Salinas, E. Aguirre, O. Cordon and M. Garcia-Silvente, “Automatic Tuning of a Fuzzy Visual System Using Evolutionary Algorithms: Single-Objective Versus Multiobjective Approaches”, IEEE Transactions on Fuzzy Systems, vol. 16, no. 2, 2008, 485–501, DOI: 10.1109/TFUZZ.2006.889954.
  • [123] R. Muñoz-Salinas, E. Aguirre and M. García-Silvente, “Detection of doors using a genetic visual fuzzy system for mobile robots”, Autonomous Robots, vol. 21, no. 2, 2006, 123–141, DOI: 10.1007/s10514-006-7847-8.
  • [124] M. Mucientes, D. L. Moreno, A. Bugarín and S. Barro, “Evolutionary learning of a fuzzy controller for wall-following behavior in mobile robotics”, Soft Computing, vol. 10, no. 10, 2006, 881–889, DOI: 10.1007/s00500-005-0014-x.
  • [125] C. Ye and D. Wang, “A Novel Navigation Method for Autonomous Mobile Vehicles”, Journal of Intelligent and Robotic Systems, vol. 32, no. 4, 2001, 361–388, DOI: 10.1023/A:1014224418743.
  • [126] F. Fathinezhad, V. Derhami and M. Rezaeian, “Supervised fuzzy reinforcement learning for robot navigation”, Applied Soft Computing, ol. 40, 2016, 33–41, DOI: 10.1016/j.asoc.2015.11.030.
  • [127] H. Omrane, M. S. Masmoudi and M. Masmoudi, “Fuzzy Logic Based Control for Autonomous Mobile Robot Navigation”, Computational Intelligence and Neuroscience, 2016, 1–10, DOI: 10.1155/2016/9548482.
  • [128] D. Gu and H. Hu, “Integration of Coordination Architecture and Behavior Fuzzy Learning in Quadruped Walking Robots”, IEEE Transactions on Systems, Man and Cybernetics, Part C (Applications and Reviews), vol. 37, no. 4, 2007, 670–681, DOI: 10.1109/TSMCC.2007.897491.
  • [129] K. M. Krishna and P. K. Kalra, “Solving the local minima problem for a mobile robot by classification of spatio-temporal sensory sequences”, Journal of Robotic Systems, vol. 17, no. 10, 2000, 549–564, DOI: 10.1002/1097-4563(200010)17:10<549::AID-ROB3>3.0.CO;2-#.
  • [130] M. Hank and M. Haddad, “A hybrid approach for autonomous navigation of mobile robots in partially-known environments”, Robotics and Autonomous Systems, vol. 86, 2016, 113–127, DOI: 10.1016/j.robot.2016.09.009.
  • [131] P. K. Mohanty and D. R. Parhi, “Navigation of autonomous mobile robot using adaptive network based fuzzy inference system”, Journal of Mechanical Science and Technology, vol. 28, no. 7, 2014, 2861–2868, DOI: 10.1007/s12206-014-0640-2.
  • [132] D. W. Kim, T. A. Lasky and S. A. Velinsky, “Autonomous multi-mobile robot system: simulation and implementation using fuzzy logic”, International Journal of Control, Automation and Systems, vol. 11, no. 3, 2013, 545–554, DOI: 10.1007/s12555-012-0096-z.
  • [133] A. Meléndez, O. Castillo, F. Valdez, J. Soria and M. Garcia, “Optimal Design of the Fuzzy Navigation System for a Mobile Robot Using Evolutionary Algorithms”, International Journal of Advanced Robotic Systems, vol. 10, no. 2, 2013, DOI: 10.5772/55561.
  • [134] C. Chen and P. Richardson, “Mobile robot obstacle avoidance using short memory: a dynamic recurrent neuro-fuzzy approach”, Transactions of the Institute of Measurement and Control, vol. 34, no. 2020-02-03, 2012, 148–164, DOI: 10.1177/0142331210366642.
  • [135] O. Obe and I. Dumitrache, “Adaptive NeuroFuzzy Controler With Genetic Training For Mobile Robot Control”, International Journal of Computers Communications & Control, vol. 7, no. 1, 2012,DOI: 10.15837/ijccc.2012.1.1429.
  • [136] Y. Wang, Y. Yang, X. Yuan, Y. Zuo, Y. Zhou, F. Yin, L. Tan, “Autonomous mobile robot navigation system designed in dynamic environment based on transferable belief model”, Measurement, vol. 44, no. 8, 2011, 1389–1405, DOI: 10.1016/j.measurement.2011.05.010.
  • [137] H. N. Pishkenari, S. H. Mahboobi and A. Alasty, “Optimum synthesis of fuzzy logic controller for trajectory tracking by differential evolution”, Scientia Iranica, vol. 18, no. 2, 2011, 261–267, DOI: 10.1016/j.scient.2011.03.021.
  • [138] K.-J. Kim and S.-B. Cho, “Evolved neural networks based on cellular automata for sensorymotor controller”, Neurocomputing, vol. 69, no. 16-18, 2006, 2193–2207, DOI: 10.1016/j.neucom.2005.07.013.
  • [139] F. Alnajjar and K. Murase, “SELF-ORGANIZATION OF SPIKING NEURAL NETWORK THAT GENERATES AUTONOMOUS BEHAVIOR INA REAL MOBILE ROBOT”, International Journal of Neural Systems, vol. 16, no. 4, 2006, 229–239, DOI: 10.1142/S0129065706000640.
  • [140] E. Tunstel, A. Howard and H. Seraji, “Rule-based reasoning and neural network perception for safe off-road robot mobility”, Expert Systems, vol. 19, no. 4, 2002, 191–200, DOI: 10.1111/1468-0394.00204.
  • [141] B. K. Patle, D. R. K. Parhi, A. Jagadeesh and S. K. Kashyap, “Matrix-Binary Codes based Genetic Algorithm for path planning of mobile robot”, Computers & Electrical Engineering, vol. 67, 2018, 708–728, DOI: 10.1016/j.compeleceng.2017.12.011.
  • [142] I. Baturone, A. Gersnoviez and Á. Barriga, “Neuro-fuzzy techniques to optimize an FPGA embedded controller for robot navigation”, Applied Soft Computing, vol. 21, 2014, 95–106, DOI: 10.1016/j.asoc.2014.03.001.
  • [143] I. Ullah, F. Ullah, Q. Ullah and S. Shin, “Integrated tracking and accident avoidance system for mobile robots”, International Journal of Control, Automation and Systems, vol. 11, no. 6, 2013, 1253–1265, DOI: 10.1007/s12555-012-0057-6.
  • [144] A. Jayasiri, G. K. I. Mann and R. G. Gosine, “Modular Supervisory Control and Hierarchical Supervisory Control of Fuzzy Discrete-Event Systems”, IEEE Transactions on Automation Science and Engineering, vol. 9, no. 2, 2012, 353–364, DOI: 10.1109/TASE.2011.2181364.
  • [145] J. K. Ong, D. Kerr and K. Bouazza-Marouf, “Design of a semi-autonomous modular robotic vehicle for gas pipeline inspection”, Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering, vol. 217, no. 2, 2003, 109–122, DOI: 10.1177/095965180321700205.
  • [146] D.-O. Kang, S.-H. Kim, H. Lee and Z. Bien, “Multiobjective Navigation of a Guide Mobile Robot for the Visually Impaired Based on Intention Inference of Obstacles”, Autonomous Robots, vol. 10, no. 2, 2001, 213–230, DOI: 10.1023/A:1008990105090.
  • [147] Á. Odry, R. Fullér, I. J. Rudas and P. Odry, “Kalman filter for mobile-robot attitude estimation: Novel optimized and adaptive solutions”, Mechanical Systems and Signal Processing, vol. 110, 2018, 569–589, DOI: 10.1016/j.ymssp.2018.03.053.
  • [148] C. Fu, A. Sarabakha, E. Kayacan, C. Wagner, R. John and J. M. Garibaldi, “Input Uncertainty Sensitivity Enhanced Nonsingleton Fuzzy Logic Controllers for Long-Term Navigation of Quadrotor UAVs”, IEEE/ASME Transactions on Mechatronics, vol. 23, no. 2, 2018, 725–734, DOI: 10.1109/TMECH.2018.2810947.
  • [149] J. Andreu-Perez, F. Cao, H. Hagras and G.-Z. Yang, “ASelf-Adaptive Online Brain–Machine Interface of a Humanoid Robot Through a General Type2 Fuzzy Inference System”, IEEE Transactions on Fuzzy Systems, vol. 26, no. 1, 2018, 101–116, DOI: 10.1109/TFUZZ.2016.2637403.
  • [150] M. R. Jabbarpour, H. Zarrabi, J. J. Jung and P. Kim, “A Green Ant-Based method for Path Planning f Unmanned Ground Vehicles”, IEEE Access, vol. 5, 2017, 1820–1832, DOI: 10.1109/ACCESS.2017.2656999.
  • [151] S. El Ferik, M. T. Nasir and U. Baroudi, “A Behavioral Adaptive Fuzzy controller of multi robots in a cluster space”, Applied Soft Computing, vol. 44, 2016, 117–127, DOI: 10.1016/j.asoc.2016.03.018.
  • [152] D. R. Parhi and P. K. Mohanty, “IWO-based adaptive neuro-fuzzy controller for mobile robot navigation in cluttered environments”,The International Journal of Advanced Manufacturing Technology, vol. 83, no. 9-12, 2016, 1607–1625,DOI: 10.1007/s00170-015-7512-5.
  • [153] M. Boujelben, C. Rekik and N. Derbel, “A MultiAgent Architecture with Hierarchical FuzzyController for a Mobile Robot”, International Journal of Robotics and Automation, vol. 30, no. 3, 2015,DOI: 10.2316/Journal.206.2015.3.206-4247.
  • [154] A. Melingui, R. Merzouki, J. B. Mbede and T. Chettibi, “A novel approach to integrate artificial ppotential field and fuzzy logic into a common framework for robots autonomous navigation”, Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering, vol. 228, no. 10, 2014, 787–801, DOI: 10.1177/0959651814548300.
  • [155] H.-C. Huang, “Intelligent Motion Control for Omnidirectional Mobile Robots Using Ant Colony Optimization”, Applied Artificial Intelligence, vol. 27, no. 3, 2013, 151–169, DOI: 10.1080/08839514.2013.768877.
  • [156] D. Nakhaeinia and B. Karasfi, “A behavior-based approach for collision avoidance of mobile robots in unknown and dynamic environments”, Journal of Intelligent & Fuzzy Systems, vol. 24, no. 2, 2013, 299–311, DOI: 10.3233/IFS-2012-0554.
  • [157] D. Herrero and H. Martínez, “Range-only fuzzy Voronoi-enhanced localization of mobile robots in wireless sensor networks”, Robotica, vol. 30, no. 7, 2012, 1063–1077, DOI: 10.1017/S0263574711001263.
  • [158] S. Djebrani, A. Benali and F. Abdessemed, “Modelling and control of an omnidirectional mobile manipulator”, International Journal of Applied Mathematics and Computer Science, vol. 22, no. 3, 2012, 601–616, DOI: 10.2478/v10006-012-0046-1.
  • [159] M. Mucientes, J. Alcalá-Fdez, R. Alcalá and J. Casillas, “A case study for learning behaviors in mobile robotics by evolutionary fuzzy systems”, Expert Systems with Applications, vol. 37, o. 2, 2010, 1471–1493,DOI: 10.1016/j.eswa.2009.06.095.
  • [160] O. Cohen and Y. Edan, “A sensor fusion framework for online sensor and algorithm selection”, Robotics and Autonomous Systems, vol. 56, no. 9, 2008, 762–776,DOI: 10.1016/j.robot.2007.12.002.
  • [161] Y. Wang, D. Mulvaney, I. Sillitoe and E. Swere, “Robot Navigation by Waypoints”, Journal of ntelligent and Robotic Systems, vol. 52, no. 2, 2008, 175–207,DOI: 10.1007/s10846-008-9209-6.
  • [162] H.-C. Huang, “FPGA-Based Parallel Metaheuristic PSO Algorithm and Its Application to Global Path Planning for Autonomous Robot Navigation”, Journal of Intelligent & Robotic Systems,vol. 76, no. 3-4, 2014, 475–488,DOI: 10.1007/s10846-013-9884-9.
  • [163] M.-F. Lee, F.-H. Chiu, C.W. de Silva, C.-Y. Shih, “Intelligent Navigation and Micro-Spectrometer Content Inspection System for a Homecare Mobile Robot”, International Journal of Fuzzy Systems, vol. 16, no. 3, 2014, 389-399.
  • [164] F. Abdessemed, M. Faisal, M. Emmadeddine,R. Hedjar, K. Al-Mutib, M. Alsulaiman and H. Mathkour, “A Hierarchical Fuzzy Control Design for Indoor Mobile Robot”, International Journal of Advanced Robotic Systems, vol. 11,no. 3, 2014,DOI: 10.5772/57434.
  • [165] M. Mucientes and A. Bugarín, “People detection through quantified fuzzy temporal rules”,Pattern Recognition, vol. 43, no. 4, 2010, 1441–1453,DOI: 10.1016/j.patcog.2009.11.008.
  • [166] B.C. Min, M.-S. Lee, D. Kim, “Fuzzy Logic Path Planner and Motion Controller by Evolutionary Programming for Mobile Robots”, International Journal of Fuzzy Systems, vol. 11, no. 3, 2009,154-163.
  • [167] H.-H. Lin and C.-C. Tsai, “Improved global localization of an indoor mobile robot via fuzzy extended information filtering”, Robotica, vol. 26, no. 2, 2008, 241–254, DOI: 10.1017/S0263574707003876.
  • [168] J. M. Alonso, L. Magdalena, S. Guillaume, M. A. Sotelo, L. M. Bergasa, M. Ocaña and R. Flores, “Knowledge-based Intelligent Diagnosis of Ground Robot Collision with Non Detectable Obstacles”, Journal of Intelligent and Robotic Systems, vol. 48, no. 4, 2007, 539–566, DOI: 10.1007/s10846-006-9125-6.
  • [169] T. V. Arredondo, W. Freund, C. Muñoz, N. Navarro and F. Quirós, “Fuzzy Motivations for Evolutionary Behavior Learning by a Mobile Robot”. In: M. Ali and R. Dapoigny (eds.), Advances in Applied Artificial Intelligence, 2006, 462–471, DOI: 10.1007/11779568_50.
  • [170] K. C. Tan, Y. J. Chen, L. F. Wang and D. K. Liu,“Intelligent sensor fusion and learning for autonomous robot navigation”, Applied Artificial Intelligence, vol. 19, no. 5, 2005, 433–456,DOI: 10.1080/08839510590901930.
  • [171] K. Demirli and M. Molhim, “Fuzzy dynamic localization for mobile robots”, Fuzzy Sets and Systems, vol. 144, no. 2, 2004, 251–283,DOI: 10.1016/S0165-0114(03)00205-7.
  • [172] J. Li, J. Chen, P. Wang and C. Li, “Sensor-Oriented Path Planning for Multiregion Surveillance with a Single Lightweight UAV SAR”, Sensors,vol. 18, no. 2, 2018,DOI: 10.3390/s18020548.
  • [173] X. Zhang, Y. Zhao, N. Deng and K. Guo, “Dynamic Path Planning Algorithm for a Mobile Robot Based on Visible Space and an Improved Genetic Algorithm”, International Journal of Advanced Robotic Systems, vol. 13, no. 3, 2016,DOI: 10.5772/63484.
  • [174] T.-H. S. Li, M.-H. Lee, C.-W. Lin, G.-H. Liou and W.-C. Chen, “Design of Autonomous and Manual Driving System for 4WIS4WID Vehicle”, IEEE Access, vol. 4, 2016, 2256–2271,DOI: 10.1109/ACCESS.2016.2548081.
  • [175] T. Huang, P. Yang, K. Yang and Y. Zhu, “Navigation of Mobile Robot in Unknown Environment Based on T-S Neuro-Fuzzy System”, International Journal of Robotics and Automation, vol. 30, no. 4, 2015, DOI: 10.2316/Journal.206.2015.4.206-4344.
  • [176] K. Das Sharma, A. Chatterjee and A. Rakshit, “Harmony search-based hybrid stable adaptive fuzzy tracking controllers for vision-based mobile robot navigation”, Machine Vision and Applications, vol. 25, no. 2, 2014, 405–419, DOI: 10.1007/s00138-013-0515-z.
  • [177] C.-Y. Wang, R.-H. Hwang and C.-K. Ting, “UbiPaPaGo: Context-aware path planning”, Expert Systems with Applications, vol. 38, no. 4, 2011, 4150–4161, OI: 10.1016/j.eswa.2010.09.077.
  • [178] C.-C. Tsai, C.-C. Chen, C.-K. Chan and Y. Y. Li, “Behavior-Based Navigation Using Heuristic Fuzzy Kohonen Clustering Network for Mobile Service Robots”, International Journal of Fuzzy Systems, vol. 12, no. 1, 2010, 25–32, DOI: 10.30000/IJFS.201003.0003.
  • [179] J.-I. Park, J.-H. Cho, M.-G. Chun, C.-K. Song, “NeuroFuzzy Rule Generation for Backing up Navigation of Car-like Mobile Robots”, International Journal of Fuzzy Systems, vol. 11, no. 3, 2009, 192–201.
  • [180] M. Gunes, A. F. Baba, “Speed and position control of autonomous mobile robot on variable trajectory depending on its curvature”, Journal of Scientific & Industrial Research, vol. 68, no. 6, 009, 513–521.
  • [181] L. McFetridge and M. Y. Ibrahim, “A new methodology of mobile robot navigation: The agoraphilic algorithm”, Robotics and Computer-Integrated Manufacturing, vol. 25, no. 3, 2009, 545–551, DOI: 10.1016/j.rcim.2008.01.008.
  • [182] Y. Fu, H. Li, Z. Jiang and S. Wang, “Double Layers Fuzzy Logic Based Mobile Robot Path Planning In Unknown Environment”, Intelligent Automation & Soft Computing, vol. 15, no. 2, 2009, 275–288, DOI: 10.1080/10798587.2009.10643031.
  • [183] N. B. Hui and D. K. Pratihar, “Camera calibration using a genetic algorithm”, Engineering Optimization, vol. 40, no. 12, 2008, 1151–1169, DOI: 10.1080/03052150802344477.
  • [184] I. Ayari and A. Chatti, “Reactive Control Using Behavior Modelling of a Mobile Robot”, International Journal of Computers Communications Control, vol. 2, no. 3, 2007, DOI: 10.15837/ijccc.2007.3.2355.
  • [185] J. R. Canning, D. B. Edwards and M. J. Anderson, “Development of a fuzzy logic controller for autonomous forest path navigation”, Transactions f the ASAE, vol. 47, no. 1, 2004, 301–310, DOI: 10.13031/2013.15855.
  • [186] D. P. T. Nanayakkara, K. Watanabe, K. Kiguchi and K. Izumi, “Evolutionary Learning of a Fuzzy Behavior Based Controller for a Nonholonomic Mobile Robot in a Class of Dynamic Environments”, Journal of Intelligent and Robotic Systems, vol. 32, no. 3, 2001, 255–277, DOI: 10.1023/A:1013939308620.
  • [187] C. Sossai, P. Bison and G. Chemello, “Sequent calculus and data fusion”, Fuzzy Sets and Systems, vol. 121, no. 3, 2001, 371–395,DOI: 10.1016/S0165-0114(00)00067-1.
  • [188] S.-Y. Kim and Y. Yang, “A self-navigating robot using Fuzzy Petri nets”, Robotics and Autonomous Systems, vol. 101, 2018, 153–165,DOI: 10.1016/j.robot.2017.11.008.
  • [189] J. Lee, “Heterogeneous-ants-based path planner for global path planning of mobile robot applications”, International Journal of Control,Automation and Systems, vol. 15, no. 4, 2017,1754–1769,DOI: 10.1007/s12555-016-0443-6.
  • [190] O. Y. Sergiyenko, M. V. Ivanov, V. V. Tyrsa,V. M. Kartashov, M. Rivas-López, D. HernándezBalbuena, W. Flores-Fuentes, J. C. RodríguezQuiñonez, J. I. Nieto-Hipólito, W. Hernandez and A. Tchernykh, “Data transferring model determination in robotic group”, Robotics and Autonomous Systems, vol. 83, 2016, 251–260,DOI: 10.1016/j.robot.2016.04.003.
  • [191] I.-H. Li, Y.-H. Chien, W.-Y. Wang and Y.-F. Kao,“Hybrid Intelligent Algorithm for Indoor Path Planning and Trajectory-Tracking Control of Wheeled Mobile Robot”, International Journal of Fuzzy Systems, vol. 18, no. 4, 2016, 595–608,DOI: 10.1007/s40815-016-0166-0.
  • [192] M. Almasri, K. Elleithy and A. Alajlan, “Sensor Fusion Based Model for Collision Free Mobile Robot Navigation”, Sensors, vol. 16, no. 1,2015, DOI: 10.3390/s16010024.
  • [193] I. H. Li, C.-C. J. Hsu and S. S. Lin, “Map building of unknown environment based on fuzzy sensor fusion of ultrasonic ranging data”, International Journal of Fuzzy Systems, vol. 16, no. 3, 2014,368–377.
  • [194] M. Martins, C. Santos, A. Frizera and R. Ceres,“Real time control of the ASBGo walker through a physical human–robot interface”, Measurement, vol. 48, 2014, 77–86, DOI: 10.1016/j.measurement.2013.10.031.
  • [195] M.-Y. Ju, S.-E. Wang and J.-H. Guo, “Path Planning Using a Hybrid Evolutionary Algorithm Based on Tree Structure Encoding”, The Scientific World Journal, 2014, 1–8,DOI: 10.1155/2014/746260.
  • [196] D. N. Nia, H. S. Tang, B. Karasfi, O. R. E. Motlagh and A. C. Kit, “Virtual force field algorithm for a behaviour-based autonomous robot in unknown environments”, Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering, vol. 225, no. 1, 2011, 51–62,DOI: 10.1243/09596518JSCE958.
  • [197] L. Doitsidis, N. C. Tsourveloudis and S. Piperidis, “Evolution of Fuzzy Controllers for Robotic Vehicles: The Role of Fitness Function Selection”, Journal of Intelligent and Robotic Systems,vol. 56, no. 4, 2009, 469–484,DOI: 10.1007/s10846-009-9332-z.
  • [198] G. Baldassarre and S. Nolfi, “Strengths and synergies of evolved and designed controllers: A study within collective robotics”, Artificial Intelligence, vol. 173, no. 7-8, 2009, 857–875,DOI: 10.1016/j.artint.2009.01.001.
  • [199] L. Ferrarini, B. M. Verbist, H. Olofsen, F. Vanpoucke, J. H. M. Frijns, J. H. C. Reiber and F. Admiraal-Behloul, “Autonomous virtual mobile robot for three-dimensional medical image exploration: Application to micro-CT cochlear images”, Artificial Intelligence in Medicine,vol. 43, no. 1, 2008, 1-15,DOI: 10.1016/j.artmed.2008.03.004.
  • [200] K.-J. Kim and S.-B. Cho, “A unified architecture for agent behaviors with selection of evolved neural network modules”, Applied Intelligence,vol. 25, no. 3, 2006, 253–268,DOI: 10.1007/s10489-006-0106-z.
  • [201] C. Fayad and P. Webb, “Development of a hybrid crisp-fuzzy logic algorithm optimised by genetic algorithms for path-planning of an autonomous mobile robot”, Journal of Intelligent & Fuzzy Systems, vol. 17, no. 1, 2006, 15–26.
  • [202] G. H. Shah Hamzei and D. J. Mulvaney, “Implementation of an Intelligent Control System Using Fuzzy ITI”, Neural Computing & Applications, vol. 9, no. 1, 2000, 12-18,DOI: 10.1007/s005210070030.
  • [203] A. K. Rath, D. R. Parhi, H. C. Das, M. K. Muni and P. B. Kumar, “Analysis and use of fuzzy intelligent technique for navigation of humanoid robot in obstacle prone zone”, Defence Technology, vol. 14, no. 6, 2018, 677–682, DOI: 10.1016/j.dt.2018.03.008.
  • [204] A. Q. Faridi, S. Sharma, A. Shukla, R. Tiwari and J. Dhar, “Multi-robot multi-target dynamic path planning using artificial bee colony and evolutionary programming in unknown environment”, Intelligent Service Robotics, vol. 11,no. 2, 2018, 171–186,DOI: 10.1007/s11370-017-0244-7.
  • [205] M. Faisal, M. Algabri, B. M. Abdelkader, H. Dhahri and M. M. Al Rahhal, “Human Expertise in Mobile Robot Navigation”, IEEE Access, vol. 6,2018, 1694–1705,DOI: 10.1109/ACCESS.2017.2780082.
  • [206] L. Wang and C. Luo, “A Hybrid Genetic Tabu Search Algorithm For Mobile Robot To Solve As/Rs Path Planning”, International Journal ofRobotics and Automation, vol. 33, no. 2, 2018, DOI: 10.2316/Journal.206.2018.2.206-5102.
  • [207] S.-C. Chen, Y.-J. Chen, I. A. E. Zaeni and C.-M. Wu,“A Single-Channel SSVEP-Based BCI with a Fuzzy Feature Threshold Algorithm in a Maze Game”, International Journal of Fuzzy Systems, vol. 19, no. 2, 2017, 553–565,DOI: 10.1007/s40815-016-0289-3.
  • [208] R. Zhao and H.-K. Lee, “Fuzzy-based Path Planning for Multiple Mobile Robots in Unknown Dynamic Environment”, Journal of Electrical Engineering and Technology, vol. 12, no. 2, 2017, 918–925,DOI: 10.5370/JEET.2017.12.2.918.
  • [209] E. A. Elsheikh, M. A. El-Bardini and M. A. Fkirin,“Practical Design of a Path Following for a Nonholonomic Mobile Robot Based on a Decentralized Fuzzy Logic Controller and MultipleCameras”, Arabian Journal for Science and Engineering, vol. 41, no. 8, 2016, 3215–3229,DOI: 10.1007/s13369-016-2147-x.
  • [210] P. Nattharith and M. S. Güzel, “Machine vision and fuzzy logic-based navigation control of a goal-oriented mobile robot”, Adaptive Behavior, vol. 24, no. 3, 2016, 168–180, DOI: 10.1177/1059712316645845.
  • [211] R. Kala and K. Warwick, “Reactive Planning of Autonomous Vehicles for Traffic Scenarios”, Electronics, vol. 4, no. 4, 2015, 739–762,DOI: 10.3390/electronics4040739.
  • [212] P. Mobadersany, S. Khanmohammadi and S. Ghaemi, “A fuzzy multi-stage path-planning method for a robot in a dynamic environment with unknown moving obstacles”, Robotica,vol. 33, no. 9, 2015, 1869–1885,DOI: 10.1017/S0263574714001064.
  • [213] J. Dou, C. Chen and P. Yang, “Genetic Scheduling and Reinforcement Learning in Multirobot Systems for Intelligent Warehouses”, Mathematical Problems in Engineering, 2015, 1–10,DOI: 10.1155/2015/597956.
  • [214] H. M. Becerra, “Fuzzy Visual Control for Memory-Based Navigation Using the Trifocal Tensor”, Intelligent Automation & Soft Computing,vol. 20, no. 2, 2014, 245–262,DOI: 10.1080/10798587.2014.906378.
  • [215] J. A. Herrera Ortiz, K. Rodríguez-Vázquez,M. A. Padilla Castañeda and F. Arámbula Cosío, “Autonomous robot navigation based on the evolutionary multi-objective optimization of potential fields”, Engineering Optimization, vol. 45, no. 1, 2013, 19–43,DOI: 10.1080/0305215X.2012.658781.
  • [216] S. Tan, S. X. Yang and A. Zhu, “A Novel Ga-Based Fuzzy Controller for Mobile Robots In Dynamic Environments With Moving Obstacles”, International Journal of Robotics and Automation,vol. 26, no. 6, 2011,DOI: 10.2316/Journal.206.2011.2.206-3447.
  • [217] M.-S. Chang and J.-H. Chou, “A Novel Machine Vision-Based Mobile Robot Navigation System in an Unknown Environment”, International Journal of Robotics and Automation, vol. 25, no. 4, 2010, DOI: 10.2316/Journal.206.2010.4.206-3372.
  • [218] K. H. Sedighi, T. W. Manikas, K. Ashenayi and R. L. Wainwright, “A Genetic Algorithm For Autonomous Navigation Using Variable-Monotone Paths”, International Journal of Robotics and Automation, vol. 24, no. 6, 2009, 367–373, DOI: 10.2316/Journal.206.2009.4.206-3252.
  • [219] U. Beldek and K. Leblebicioğlu, “Strategy creation, decomposition and distribution in particle navigation”, Information Sciences, vol. 177, no. 3, 2007, 755–770, DOI: 10.1016/j.ins.2006.07.008.
  • [220] X. Yang, M. Moallem and R. V. Patel, “A SensorBased Navigation Algorithm for a Mobile Robot Using Fuzzy Logic”, International Journal of Robotics and Automation, vol. 21, no. 2, 2006, 129–140,DOI: 10.2316/Journal.206.2006.2.206-2797.
  • [221] J. Yu, Z. Cai and Z. Duan, “Fuzzy Likelihood Estimation Based Map Matching for Mobile RobotSelf-localization”. In: L. Wang, L. Jiao, G. Shi,X. Li and J. Liu (eds.), Fuzzy Systems and Knowledge Discovery, 2006, 846–855,DOI: 10.1007/11881599_104.
  • [222] H. Hu and D. Gu, “Hybrid learning architecture for fuzzy control of quadruped walking robots”,International Journal of Intelligent Systems,vol. 20, no. 2, 2005, 131–152,DOI: 10.1002/int.20059.
  • [223] N. E. Hodge, L. Z. Shi and M. B. Trabia, “A distributed fuzzy logic controller for an autonomous vehicle”, Journal of Robotic Systems, vol. 21,no. 10, 2004, 499–516,DOI: 10.1002/rob.20032.
  • [224] E. Tunstel and A. Howard, “Approximate reasoning for safety and survivability of planetary rovers”, Fuzzy Sets and Systems, vol. 134, no. 1,2003, 27–46,DOI: 10.1016/S0165-0114(02)00228-2.
  • [225] F. Hoffmann, “An Overview on Soft Computing in Behavior Based Robotics”. In: T. Bilgiç, B. De Baets and O. Kaynak (eds.), Fuzzy Sets and Systems — IFSA 2003, 2003, 544–551,DOI: 10.1007/3-540-44967-1_65.
  • [226] J. K. Ong, K. Bouazza-Marouf and D. Kerr, “Fuzzy logic control for use in in-pipe mobile robotic system navigation”, Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering, vol. 217,no. 5, 2003, 401–419,DOI: 10.1177/095965180321700506.
  • [227] K. Ward and A. Zelinsky, “Acquiring Mobile Robot Behaviors by Learning Trajectory Velocities”, Autonomous Robots, vol. 9, no. 2, 2000, 113–133,DOI: 10.1023/A:1008914200569.
  • [228] S. Bonadies, N. Smith, N. Niewoehner, A. S. Lee,A. M. Lefcourt and S. Andrew Gadsden, “Development of Proportional–Integral–Derivative and Fuzzy Control Strategies for Navigation in Agricultural Environments”, Journal of Dynamic Systems, Measurement, and Control, vol. 140,no. 6, 2018,DOI: 10.1115/1.4038504.
  • [229] T. Y. Abdalla, A. A. Abed and A. A. Ahmed, “Mobile robot navigation using PSO-optimized fuzzy artificial potential field with fuzzy control”, Journal of Intelligent & Fuzzy Systems,vol. 32, no. 6, 2017, 3893–3908,DOI: 10.3233/IFS-162205.
  • [230] D. Luviano and W. Yu, “Continuous-time path planning for multi-agents with fuzzy reinforcement learning”, Journal of Intelligent & Fuzzy Systems, vol. 33, no. 1, 2017, 491–501,OI: 10.3233/JIFS-161822.
  • [231] A. Karray, M. Njah, M. Feki and M. Jallouli, “Intelligent mobile manipulator navigation using hybrid adaptive-fuzzy controller”, Computers & Electrical Engineering, vol. 56, 2016, 773–783,DOI: 10.1016/j.compeleceng.2016.09.007.
  • [232] K. Al-Muteb, M. Faisal, M. Emaduddin, M. Arafah, M. Alsulaiman, M. Mekhtiche, R. Hedjar,H. Mathkoor, M. Algabri and M. A. Bencherif, “An autonomous stereovision-based navigation system (ASNS) for mobile robots”, Intelligent Service Robotics, vol. 9, no. 3, 2016, 187–205,DOI: 10.1007/s11370-016-0194-5
  • [233] M. Algabri, H. Mathkour, H. Ramdane, M. Alsulaiman, K. Al-Mutib, “Self-learning Mobile Robot Navigation in Unknown Environment Using Evolutionary Learning”, Journal Of Universal Computer Science, Volume: 20, Issue:10, 2014, 1459–1468,DOI: 10.3217/jucs-020-10-1459.
  • [234] K. Prema, N. S. Kumar and S. S. Dash, “Online Control of DC Motors Using Fuzzy Logic Controller for Remote Operated Robots”, Journal of Electrical Engineering and Technology, vol. 9, no. 1, 2014, 352–362, DOI: 10.5370/JEET.2014.9.1.352.
  • [235] H. Šiljak, “Inverse Matching-Based Mobile Robot Following Algorithm Using Fuzzy Logic”, International Journal of Robotics and Automation, vol. 29, no. 6, 2014, 369–377, DOI: 10.2316/Journal.206.2014.4.206-4036.
  • [236] P. Kannan, S. K. Natarajan and S. S. Dash, “Design and Implementation of Fuzzy Logic Controller for Online Computer Controlled Steering System for Navigation of a Teleoperated Agricultural Vehicle”, Mathematical Problems in Engineering, 2013, 1–10,DOI: 10.1155/2013/590861.
  • [237] M. Shayestegan, M. H. Marhaban, S. Shafie and A. S. b. Din, “Fuzzy Logic-Based Robot Navigation in Static Environment with Dead Cycle Obstacles”, International Journal of Robotics and Automation, vol. 28, no. 6, 2013, 379–388,DOI: 10.2316/Journal.206.2013.4.206-3922.
  • [238] M. Jamshidi, J. Gomez, S. Aldo, B. Jaimes, “Intelligent Control of UAVs For Consensus-Based and Network Controlled Applications”, Applied and Computational Mathematics an International Journal, vol. 10, no. 1, 2011, 35–64.
  • [239] D. R. Parhi and M. K. Singh, “Navigational path analysis of mobile robots using an adaptive neuro-fuzzy inference system controller in a dynamic environment”, Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, vol. 224,no. 6, 2010, 1369–1381, DOI: 10.1243/09544062JMES1751.
  • [240] N. B. Hui and D. K. Pratihar, “Soft ComputingBased Navigation Schemes for a Real Wheeled Robot Moving Among Static Obstacles”, Journal of Intelligent and Robotic Systems, vol. 51, no. 3, 2008, 333–368, DOI: 10.1007/s10846-007-9190-5.
  • [241] I. P. Anderson, A. C. Carlson, D. B. Edwards,M. J. Anderson and J. J. Feeley, “An Autonomous Forest Robot That Uses a Hierarchical, Fuzzy Logic Controller”, Transactions of the ASAE,vol. 48, no. 4, 2005, 1603–1617,DOI: 10.13031/2013.19175.
  • [242] S.-J. Kim, W.-K. Choi and H.-T. Jeon, “Intelligent Robot Control with Personal Digital Assistants Using Fuzzy Logic and Neural Network”. In:M. G. Negoita, R. J. Howlett and L. C. Jain (eds.),Knowledge-Based Intelligent Information and Engineering Systems, 2004, 589–595,DOI: 10.1007/978-3-540-30134-9_79.
  • [243] Y. D. Kwon and J. S. Lee, “On-Line Evolutionary Optimization of Fuzzy Control System based on Decentralized Population”, Intelligent Automation & Soft Computing, vol. 6, no. 2, 2000, 135–146,DOI: 10.1080/10798587.2000.10768166.
  • [244] A. Kumar, P. B. Kumar and D. R. Parhi, “Intelligent Navigation of Humanoids in Cluttered Environments Using Regression Analysis and Genetic Algorithm”, Arabian Journal for Science and Engineering, vol. 43, no. 12, 2018, 7655–7678,DOI: 10.1007/s13369-018-3157-7.
  • [245] J.-Y. Jhang, C.-J. Lin, C.-T. Lin and K.-Y. Young,“Navigation Control of Mobile Robots Using an Interval Type-2 Fuzzy Controller Based on Dynamic-group Particle Swarm Optimization”, International Journal of Control, Automation and Systems, vol. 16, no. 5, 2018, 2446–2457,DOI: 10.1007/s12555-017-0156-5.
  • [246] T.-C. Lin, C.-C. Chen and C.-J. Lin, “Wall-following and Navigation Control of Mobile Robot Using Reinforcement Learning Based on Dynamic Group Artificial Bee Colony”, Journal of Intelligent & Robotic Systems, vol. 92, no. 2, 2018,343–357,DOI: 10.1007/s10846-017-0743-y.
  • [247] M. S. Miah, J. Knoll and K. Hevrdejs, “Intelligent Range-Only Mapping and Navigation for Mobile Robots”, IEEE Transactions on Industrial Informatics, vol. 14, no. 3, 2018, 1164–1174,DOI: 10.1109/TII.2017.2780247.
  • [248] T.-C. Lin, C.-C. Chen and C.-J. Lin, “Navigation control of mobile robot using interval type-2 neural fuzzy controller optimized by dynamic group differential evolution”, Advances in Mechanical Engineering, vol. 10, no. 1, 2018,DOI: 10.1177/1687814017752483.
  • [249] P.-H. Kuo, T.-H. S. Li, G.-Y. Chen, Y.-F. Ho and C.-J. Lin, “A migrant-inspired path planning algorithm for obstacle run using particle swarm optimization, potential field navigation, and fuzzy logic controller”, The Knowledge Engineering Review, vol. 32, 2017,DOI: 10.1017/S0269888916000151.
  • [250] D. G. Perumal, S. Srinivasan, B. Subathra, G. Saravanakumar and R. Ayyagari, “MILP based autonomous vehicle path-planning controller or unknown environments with dynamic obstacles”, International Journal of Heavy Vehicle Systems, vol. 23, no. 4, 2016,DOI: 10.1504/IJHVS.2016.079272.
  • [251] P. K. Panigrahi, S. Ghosh and D. R. Parhi, “Navigation of autonomous mobile robot using different activation functions of wavelet neural network”, Archives of Control Sciences, vol. 25, no. 1, 2015, 21–34,DOI: 10.1515/acsc-2015-0002.
  • [252] H. Monfared and S. Salmanpour, “Generalized intelligent Water Drops algorithm by fuzzy local search and intersection operators on partitioning graph for path planning problem”, Journal of Intelligent & Fuzzy Systems, vol. 29, no. 2, 2015, 975–986,DOI: 10.3233/IFS-151661.
  • [253] R. Kala, “Navigating Multiple Mobile Robots without Direct Communication”, International Journal of Intelligent Systems, vol. 29, no. 8,2014, 767–786,DOI: 10.1002/int.21662.
  • [254] T. V. Arredondo, W. Freund, N. Navarro-Guerrero and P. Castillo, “Fuzzy Motivations in a Multiple Agent Behaviour-Based Architecture”,International Journal of Advanced Robotic Systems, vol. 10, no. 8, 2013,DOI: 10.5772/56578.
  • [255] H. T. Leidenfrost, T. Tate, J. R. Canning, M. J. Anderson, T. Soule, D. B. Edwards, J. F. Frenzel, “Autonomous Navigation of Forest Trails By an Industrial-Size Robot”, Transactions of the ASABE, Volume: 56, Issue: 4, 2013, Pages:1273–1290, DOI: 10.13031/trans.56.9684.
  • [256] T. Ferrauto, D. Parisi, G. Di Stefano and G. Baldassarre, “Different Genetic Algorithms and the Evolution of Specialization: A Study with Groups of Simulated Neural Robots”, Artificial Life, vol. 19, no. 2, 2013, 221–253,DOI: 10.1162/ARTL_a_00106.
  • [257] W. Benn and S. Lauria, “Robot Navigation Control Based on Monocular Images: An Image Processing Algorithm for Obstacle Avoidance Decisions”, Mathematical Problems in Engineering, 2012, 1–14, DOI: 10.1155/2012/240476.
  • [258] S. K. Hong, S. Moon and Y.-S. Ryuh, “Angle measurements for mobile robots with filtering of short-term noise in MEMS gyroscopes”, Transactions of the Institute of Measurement and Control, vol. 33, no. 6, 2011, 650–664,DOI: 10.1177/0142331209342194.
  • [259] P. T. Zacharia, “An Adaptive Neuro-fuzzy Inference System for Robot Handling Fabrics with Curved Edges towards Sewing”, Journal of Intelligent and Robotic Systems, vol. 58, no. 3–4, 2010, 193–209,DOI: 10.1007/s10846-009-9362-6.
  • [260] M. Medeiros, L. M. Gonçalves and A. Frery, “Using Fuzzy Logic to Enhance Stereo Matching in Multiresolution Images”, Sensors, vol. 10, no. 2, 2010, 1093–1118,DOI: 10.3390/100201093.
  • [261] N. S. Tlale, “Fuzzy logic controller with slip detection behaviour for Mecanum-wheeled AGV”, Robotica, vol. 23, no. 4, 2005, 455–456,DOI: 10.1017/S0263574705001888.
  • [262] M.-W. Seo, Y.-J. Kim and M.-T. Lim, “Door Traversing for a Vision-Based Mobile Robot Using PCA”. In: R. Khosla, R. J. Howlett and L. C. Jain (eds.), Knowledge-Based Intelligent Information and Engineering Systems, 2005, 525–531, DOI: 10.1007/11554028_73.
  • [263] X. J. Wu, Q. Li and K. H. Heng, “Development of a general manipulator path planner using fuzzy reasoning”, Industrial Robot: An International Journal, vol. 32, no. 3, 2005, 248–258,DOI: 10.1108/01439910510593947.
  • [264] O. Miglino and R. Walker, “Evolving an actionbased mechanism for the interpretation of geometrical clues during robot navigation”, Connection Science, vol. 16, no. 4, 2004, 267–281,DOI: 10.1080/09540090412331314777.
  • [265] M. Tedder, D. Chamulak, L.-P. Chen, S. Nair,A. Shvartsman, I. Tseng and C.-J. Chung, “An affordable modular mobile robotic platform with fuzzy logic control and evolutionary artificial neural networks”, Journal of Robotic Systems, vol. 21, no. 8, 2004, 419–428, DOI: 10.1002/rob.20023.
  • [266] E. Dönmez, A. F. Kocamaz and M. Dirik, “A Vision-Based Real-Time Mobile Robot Controller Design Based on Gaussian Function for Indoor Environment”, Arabian Journal for Science and Engineering, vol. 43, no. 12, 2018, 7127–7142, DOI: 10.1007/s13369-017-2917-0.
  • [267] C.-H. Lin, S.-H. Wang and C.-J. Lin, “Interval Type-2 Neural Fuzzy Controller-Based Navigation of Cooperative Load-Carrying Mobile Robots in Unknown Environments”, Sensors, vol. 18, no. 12, 2018,DOI: 10.3390/s18124181.
  • [268] E. Clemente, M. Meza-Sánchez, E. Bugarin and A. Y. Aguilar-Bustos, “Adaptive Behaviors in Autonomous Navigation with Collision Avoidance and Bounded Velocity of an Omnidirectional Mobile Robot: A Control Theory with Genetic Programming Approach”, Journal of ntelligent & Robotic Systems, vol. 92, no. 2, 2018, 359–380, DOI: 10.1007/s10846-017-0751-y.
  • [269] C.-L. Hwang and Y. Lee, “Tracking Design of an Omni-Direction Autonomous Ground Vehicle y Hierarchical Enhancement Using Fuzzy Second-Order Variable Structure Control”, Journal of Dynamic Systems, Measurement, and Control,vol. 140, no. 9, 2018, DOI: 10.1115/1.4039277.
  • [270] A. Rengifo, F. E. Segura-Quijano and N. Quijano,An Affordable Set of Control System Laboratories Using A Low-Cost Robotic Platform”, IEEE/ASME Transactions on Mechatronics, vol. 23,no. 4, 2018, 1705–1715,DOI: 10.1109/TMECH.2018.2843888.
  • [271] L. A. Dias, R. W. de Oliveira Silva, P. C. da Silva Emanuel, A. F. Filho and R. T. Bento, “Application of the Fuzzy Logic for the Development of Automnomous Robot with Obstacles Deviation”, International Journal of Control, Automation and Systems, vol. 16, no. 2, 2018, 823–833,DOI: 10.1007/s12555-017-0055-9.
  • [272] A. Aouf, L. Boussaid and A. Sakly, “TLBO-Based Adaptive Neurofuzzy Controller for Mobile Robot Navigation in a Strange Environment”,Computational Intelligence and Neuroscience,2018, 1–8,DOI: 10.1155/2018/3145436.
  • [273] J.-Y. Jhang, C.-J. Lin, T.-C. Lin, C.-C. Chen and K.-Y. Young, “Using Interval Type-2 Recurrent Fuzzy Cerebellar Model Articulation Controller Based on Improved Differential Evolution for Cooperative Carrying Control of Mobile Robots”, Sensors and Materials, vol. 30, no. 11,2018,DOI: 10.18494/SAM.2018.2052.
  • [274] M. Algabri, H. Mathkour, M. A. Mekhtiche,M. A. Bencherif, M. Alsulaiman, M. A. Arafah and H. Ghaleb, “Wireless vision-based fuzzy controllers for moving object tracking using a quadcopter”, International Journal of Distributed Sensor Networks, vol. 13, no. 4, 2017,DOI: 10.1177/1550147717705549.
  • [275] A. H. M. Findi, M. H. Marhaban, R. Kamil and M. K. Hassan, “Collision Prediction based Genetic Network Programming-Reinforcement Learning for Mobile Robot Navigation in Unknown Dynamic Environments”, Journal of Electrical Engineering and Technology, vol. 12, no. 2, 2017, 890–903,DOI: 10.5370/JEET.2017.12.2.890.
  • [276] L. Li, C.-J. Lin, M.-L. Huang, S.-C. Kuo and Y.-R. Chen, “Mobile robot navigation control using recurrent fuzzy cerebellar model articulation controller based on improved dynamic artificial bee colony”, Advances in Mechanical Engineering, vol. 8, no. 11, 2016,DOI: 10.1177/1687814016681234.
  • [277] S.-Y. Chiang, “Vision-based obstacle avoidance system with fuzzy logic for humanoid robots”,The Knowledge Engineering Review, vol. 32,2017,DOI: 10.1017/S0269888916000084.
  • [278] A. Z. Zambom, J. A. A. Collazos and R. Dias, “Constrained optimization with stochastic feasibility regions applied to vehicle path planning”,Journal of Global Optimization, vol. 64, no. 4,2016, 803–823,DOI: 10.1007/s10898-015-0353-9.
  • [279] E. Baklouti, N. B. Amor and M. Jallouli, “Autonomous wheelchair navigation with real time obstacle detection using 3D sensor”, Automatika,vol. 57, no. 3, 2016, 761–773,DOI: 10.7305/automatika.2017.02.1421.
  • [280] H. Miloud and H. Abdelouahab, “Improving mobile robot navigation by combining fuzzy reasoning and virtual obstacle algorithm”, Journal of Intelligent & Fuzzy Systems, vol. 30, no. 3,2016, 1499–1509,DOI: 10.3233/IFS-151857.
  • [281] N. Ortigosa and S. Morillas, “Fuzzy Free Path Detection from Disparity Maps by Using LeastSquares Fitting to a Plane”, Journal of Intelligent & Robotic Systems, vol. 75, no. 2, 2014, 313–330,DOI: 10.1007/s10846-013-9997-1.
  • [282] S. A. Rahim, A. M. Yusof and T. Bräunl, “Genetically evolved action selection mechanism in a behavior-based system for target tracking”,Neurocomputing, vol. 133, 2014, 84–94,DOI: 10.1016/j.neucom.2013.11.028.
  • [283] H. Miao and X. Huang, “A Heuristic Field Navigation Approach for Autonomous Underwater Vehicles”, Intelligent Automation & Soft Computing, vol. 20, no. 1, 2014, 15–32,DOI: 10.1080/10798587.2013.872326.
  • [284] O. Azouaoui, N. Ouadah, I. Mansour, A. Semani,S. Aouana and D. Chabi, “Soft-computing based navigation approach for a bi-steerable mobile robot”, Kybernetes, vol. 42, no. 2, 2013, 241–267,DOI: 10.1108/03684921311310594.
  • [285] L. T. Ngo, “General type-2 fuzzy logic systems based on refinement constraint triangulated irregular network”, Journal of Intelligent & Fuzzy Systems, vol. 25, no. 3, 2013, 771–784,DOI: 10.3233/IFS-120683.
  • [286] Y. Cheng, Y. Fan and M. Huang, “Innovative Intelligent Navigation System by Applying Fuzzy Logic and Cell Assemblies in Rescuing Robot”,Applied Artificial Intelligence, vol. 26, no. 3,2012, 183–203,DOI: 10.1080/08839514.2011.613572.
  • [287] D. R. Parhi and M. K. Singh, “Heuristic-rulebased hybrid neural network for navigation of a mobile robot”, Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, vol. 224, no. 7, 2010,1103–1118,DOI: 10.1243/09544054JEM1736.
  • [288] H. Xue and H.-X. Ma, “Swarm intelligence based dynamic obstacle avoidance for mobile robots under unknown environment using WSN”,Journal of Central South University of Technology, vol. 15, no. 6, 2008, 860–868,DOI: 10.1007/s11771-008-0158-9.
  • [289] O. M. Al-Jarrah and Y. M. Tashtoush, “Mobile Robot Navigation Using Fuzzy Logic”, Intelligent Automation & Soft Computing, vol. 13, no. 2,2007, 211–228,DOI: 10.1080/10798587.2007.10642960.
  • [290] L. Huang, D. He, and S. X. Yang, “Segmentation on Ripe Fuji Apple with Fuzzy 2D Entropy based on 2D histogram and GA Optimization,” Intelligent Automation & Soft Computing, vol. 19, no. 3, 239–251, 2013,10.1080/10798587.2013.823755.
  • [291] S. B. Saoud, L. Nciri and M. Ghrissi, “Path-Tracking and Parking Manoeuvre Control of an Industrial Tricycle Robot”, International Journal of Robotics and Automation, vol. 20, no. 4, 2005,DOI: 10.2316/Journal.206.2005.4.206-2905.
  • [292] M. Lin, J. Zhu and Z. Sun, “Learning Obstacle Avoidance Behavior Using Multi-agent Learnng with Fuzzy States”. In: C. Bussler and D. Fensel (eds.), Artificial Intelligence: Methodology, Systems, and Applications, 2004, 389–398,DOI: 10.1007/978-3-540-30106-6_40.
  • [293] J. M. Armingol, A. de la Escalera, L. Moreno and M. A. Salichs, “Mobile robot localization using a non-linear evolutionary filter”, Advanced Robotics, vol. 16, no. 7, 2002, 629–652,DOI: 10.1163/15685530260390755.
  • [294] D. K. Pratihar and W. Bibel, “Path Planning for Cooperating Robots Using a GA-Fuzzy Approach”. In: M. Beetz, J. Hertzberg, M. Ghallab and M. E. Pollack (eds.), Advances in Plan-Based Control of Robotic Agents, 2002, 193–210,DOI: 10.1007/3-540-37724-7_12.
  • [295] A. Maoudj, A. Hentout, B. Bouzouia and R. Toumi, “On-Line Fault-Tolerant Fuzzy-Based Path Planning and Obstacles Avoidance Approach for Manipulator Robots”, International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, vol. 26, no. 5, 2018, 809–838,DOI: 10.1142/S0218488518500368.
  • [296] C.-F. Juang, Y.-H. Jhan, Y.-M. Chen and C.-M. Hsu,“Evolutionary Wall-Following Hexapod Robot Using Advanced Multiobjective Continuous Ant Colony Optimized Fuzzy Controller”, IEEE Transactions on Cognitive and Developmental Systems, vol. 10, no. 3, 2018, 585–594, DOI: 10.1109/TCDS.2017.2681181.
  • [297] J. Zeng, L. Wan, Y. Li, Z. Zhang, Y. Xu and G. Li, “Robust composite neural dynamic Surface control for the path following of unmanned marine surface vessels with unknown disturbances”, International Journal of Advanced Robotic Systems, vol. 15, no. 4, 2018,DOI: 10.1177/1729881418786646.
  • [298] D. Ayedi, M. Boujelben and C. Rekik, “A Multiagent Architecture for Mobile Robot Navigation Using Hierarchical Fuzzy and Sliding Mode Controllers”, Mathematical Problems in Engineering, 2018, 1–11,DOI: 10.1155/2018/9315925.
  • [299] K. W. Schmidt and Y. S. Boutalis, “Fuzzy Discrete Event Systems for Multiobjective Control: Framework and Application to Mobile Robot Navigation”, IEEE Transactions on Fuzzy Systems, vol. 20, no. 5, 2012, 910–922,DOI: 10.1109/TFUZZ.2012.2189219.
  • [300] X. Yang, R. V. Patel and M. Moallem, “A Fuzzy–Braitenberg Navigation Strategy for Differential Drive Mobile Robots”, Journal of Intelligent and Robotic Systems, vol. 47, no. 2, 2006, 101–124,DOI: 10.1007/s10846-006-9055-3.
  • [301] W.-S. Lin, C.-L. Huang and M.-K. Chuang, “Hierarchical fuzzy control for autonomous navigation of wheeled robots”, IEEE Proceedings –Control Theory and Applications, vol. 152, no. 5,2005, 598–606,DOI: 10.1049/ip-cta:20059062.
  • [302] D. K. Pratihar, K. Deb and A. Ghosh, “Optimal turning gait of a six-legged robot using a GAfuzzy approach”, Artificial Intelligence for Engineering Design, Analysis and Manufacturing, vol. 14, no. 3, 2000, 207–219, DOI: 10.1017/S0890060400143033.
  • [303] J. B. Mbede, W. Wei and Q. Zhang, “Fuzzy and Recurrent Neural Network Motion Control among Dynamic Obstacles for Robot Manipulators”, Journal of Intelligent and Robotic Systems,vol. 30, no. 2, 2001, 155–177,DOI: 10.1023/A:1008194912825.
  • [304] Q. Chen and Ü. Özgüner, “Intelligent off-road navigation algorithms and strategies of Team Desert Buckeyes in the DARPA Grand Challenge”, Journal of Field Robotics, vol. 23, no. 9,2006, 729–743,DOI: 10.1002/rob.20138.
  • [305] W. Wei, J. B. Mbede and Q. Zhang, “Fuzzy Sensor-Based Motion Control among Dynamic Obstacles for Intelligent Rigid-Link Electrically Driven Arm Manipulators”, Journal of Intelligent and Robotic Systems, vol. 30, no. 1, 2001,49–71,DOI: 10.1023/A:1008190612246.
  • [306] R. Liu, Y.-X. Wang and L. Zhang, “An FDES-Based Shared Control Method for Asynchronous Brain-Actuated Robot”, IEEE Transactions on Cybernetics, vol. 46, no. 6, 2016, 1452–1462,DOI: 10.1109/TCYB.2015.2469278.
  • [307] R.-J. Wai, C.-M. Liu and Y.-W. Lin, “Robust path tracking control of mobile robot via dynamic petri recurrent fuzzy neural network”, Soft Computing, vol. 15, no. 4, 2010, 743–767,DOI: 10.1007/s00500-010-0607-x.
  • [308] M. Mahapatra, “On the validity of the theory of exponential growth of scientific literature,”Proceedings of the 15th IASLIC conference,1985, 61–70.
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2020).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-6c8045ef-3423-4a64-b352-fa91ed0ebcff
JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.