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An exoskeleton arm optimal configuration determination using inverse kinematics and genetic algorithm

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
This paper deals with the kinematic modelling of an arm exoskeleton used for human rehabilitation. The biomechanics of the arm was studied and the 9 Degrees of Freedom model was obtained. The particular (optimal) exoskeleton arm configuration is needed, depending on patient abilities and possibility or other users activity. Methods: The model of upper arm was obtained by using Denavit–Hartenberg notation. The exoskeleton human arm was modelled in MathWorks package. The multicriteria optimization procedure was formulated to plan the motion of trajectory. In order to find the problem solution, an artificial intelligence method was used. Results: The optimal solutions were found applying a genetic algorithm. Two variants of motion with and the visualization of the change of joints angles were shown. By the use of genetic algorithms, movement trajectory with the Pareto-optimum solutions has been presented as well. Creating a utopia point, it was possible to select only one solution from Pareto-optimum results. Conclusions: The obtained results demonstrate the efficiency of the proposed approach that can be utilized to analyse the kinematics and dynamics of exoskeletons using the dedicated design process. Genetic algorithm solution could be implemented to command actuators, especially in the case of multi-criteria problems. Moreover, the effectiveness of this method should be evaluated in the future by real experiments.
Rocznik
Strony
45--53
Opis fizyczny
Bibliogr. 25 poz., rys., tab., wykr.
Twórcy
  • Koszalin University of Technology, Faculty of Technology and Education, Department of Mechatronics and Applied Mechanics, Koszalin, Poland
  • Koszalin University of Technology, Faculty of Technology and Education, Department of Mechatronics and Applied Mechanics, Koszalin, Poland
Bibliografia
  • [1] ALRASHIDI M., YILDIZ I., VANAT Q., ESAT M., CHIZARI M., Kinematics Analysis of the Elbow Joint; Comparison of the Kinematics of the Left and Right Elbow, Proceedings of the World Congress on Engineering, Jul. 6–8, 2011, 2681–2684.
  • [2] ASFOUR T., DILLMANN R., Human-like Motion of a Humanoid Robot Arm Based on a Closed-Form Solution of the Inverse Kinematics Problem, IEEE/RSJ Intern. Conf. on Intelligent Robots and Systems, USA, 2003, 1407–1412.
  • [3] BLAZEJEWSKI A., Reduction of low frequency acoustical resonances inside bounded space using eigenvalue problem solutions and topology optimization, Theoretical and Experimental Analysis. Springer Proceedings in Mathematics and Statistics, 2016, 182, 15–25.
  • [4] BLAZEJEWSKI A., Topology optimization of a bounded space for a vibroacoustical problem in a low frequency, Solid State Phenomena, 2016, 248, 41–48.
  • [5] CORKE P., Robotics, Vision and Control, Fundamental Algorithms in MATLAB, Springer, 2011.
  • [6] CROWELL H.P., Human Engineering Design Guidelines for a Powered, Full Body Exoskeleton, U.S. Army Research Laboratory, 1995.
  • [7] CULMER P., JACKSON A., LEVESLEY M., SAVAGE J., RICHARDSON R., COZENS J., BHAKTA B., An admittance control scheme for a robotic upper-limb stroke rehabilitation system, Engineering in Medicine and Biology 27th Annual Conference, 2005, 5081–5084.
  • [8] DAVIES D.V., DAVIES F., Gray’s Anatomy, Green and Co., Ltd., 33 ed., 1962.
  • [9] DIJKSTRA E.J., Upper Limb Project – Modeling of the Upper Limb, Department of Engineering Technology, University of Twente, 2010.
  • [10] GLOWINSKI S., KRZYZYNSKI T., PECOLT S., MACIEJEWSKI I., Design of motion trajectory of an arm exoskeleton, Archive of Applied Mechanics, 2015, 85(1), 75–87.
  • [11] GLOWINSKI S., KRZYZYNSKI T., An inverse kinematic algorithm for the human leg, Journal of Theoretical and Applied Mechanics, 2016, 54(1), 53–61.
  • [12] GOEHLER C.M., Design of A Humanoid Shoulder-Elbow Complex, Dissertation, Aerospace And Mechanical Engineering Notre Dame, Indiana, 2007.
  • [13] JANSEN J., RICHARDSON B., PIN F., LIND R., BIRDWELL J., Exoskeleton for Soldier Enhancement Systems Feasibility Study, Oak Ridge National Laboratory, Tennessee, 2000.
  • [14] JAZAR R.N., Theory of Applied Robotics, Springer, 2007.
  • [15] LUTTGENS K., WELLS K.F., Kinesiology: Scientific Basis of Human Motion, 6th ed. Philadelphia: Saunders College Publishing, 1982.
  • [16] MILICEVIC I., SLAVKOVIC R., GOLUBOVIC D., Industrial Robot Models Designing and Analysis with Application of Matlab Software, Machine Design, 2007.
  • [17] PIETRASZEWSKI B., WINIARSKI S., JAROSZCZUK S., Three-Dimensional Human Gait Pattern-Reference Data for normal Men, Acta of Bioengineering and Biomechanics, 2012, 14(3), 9–16.
  • [18] PONS J.L., Wearable Robots: Biomechatronic Exoskeletons, John Wiley and Sons, 2008.
  • [19] ROCON E., PONS J.L., Exoskeletons in Rehabilitation Robotics, Tremor Suppression, Springer, 2011.
  • [21] SPONG M.W., HUTCHINSON S., VIDYASAGAR M., Robot modeling and control, Wiley, 2006.
  • [22] STASZKIEWICZ R., CHWAŁA W., FORCZEK W., LASKA J., Influence of surface on Kinematic Gait Parameters and Lower Extremity Joints Mobility, Acta of Bioengineering and Biomechanics, 2012, 14(1), 75–82.
  • [23] TZONG-MING W., DAR-ZEN C., Design of an Exoskeleton for Strengthening the Upper Limb Muscle for Overextension Injury Prevention, Mechanism and Machine Theory, 2011, 46, 1825–1839.
  • [24] WIERZCHOLSKI K., MISZCZAK A., Magneto-therapy of human joint cartilage, Acta of Bioengineering and Biomechanics, 2017, 19(1), 115–124.
  • [25] WIERZCHOLSKI K., Time dependent human hip joint lubrication for periodic motion with stochastic asymmetric density function, Acta of Bioengineering and Biomechanics, 2014, 16(1), 83–97.
Uwagi
Błędna numeracja bibliografii.
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-0db35894-d03e-4e3a-b977-e5aaa0e728ac
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