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Projekt systemu mapowania terenu do tanich eksploracji Roboty oparte na Stereo Vision
Języki publikacji
Abstrakty
This paper proposes a low-cost system for terrestrial mapping and exploration of inaccessible or subterranean environments by using stereo vision with two cameras, image processing and a developed algorithm based on disparity maps that reconstructs a 3D map of the explored environment. The tests were performed on a robot with two stereo vision cameras mounted on a turret with 360° freedom of movement. The tests showed that this proposed system allows to visualize the depth of the objects around the robot and builds a 360° scenario of the explored place
W artykule zaproponowano niedrogi system do mapowania naziemnego i eksploracji niedostępnych lub podziemnych środowisk przy użyciu stereowizyjnego widzenia z dwiema kamerami, przetwarzania obrazu i opracowanego algorytmu opartego na mapach rozbieżności, który rekonstruuje trójwymiarową mapę badanego środowiska. Testy przeprowadzono na robocie z dwiema kamerami stereowizyjnymi zamontowanymi na wieżyczce ze swobodą ruchu 360°. Testy wykazały, że proponowany system pozwala na wizualizację głębokości obiektów wokół robota i buduje scenariusz 360° badanego miejsca.
Wydawca
Czasopismo
Rocznik
Tom
Strony
270--275
Opis fizyczny
Bibliogr. 26 poz., rys.
Twórcy
- Universidad Nacional de San Agustin de Arequipa, Peru
- Universidad Nacional de San Agustin de Arequipa, Peru
- Universidad Nacional de San Agustin de Arequipa, Peru
autor
- Universidad Nacional de San Agustin de Arequipa, Peru
autor
- Universidad Nacional de San Agustin de Arequipa, Peru
Bibliografia
- [1] T. Yamamoto, Y. Takagi; A. Ochiai, K. Iwamoto, Y. Itozawa, Y. Asahara, K. Ikeda. Human Support Robot as Research Platform of Domestic Mobile Manipulator. Springer: Cham, Switzerland, 2019; Volume 11531.
- [2] Rafael Verano M, Jose Caceres S, Abel Arenas H, Andres Montoya A, Joseph Guevara M, Jarelh Galdos B and Jesus Talavera S, Development of a Low-Cost Teleoperated Explorer Robot (TXRob) International Journal of Advanced Computer Science and Applications(IJACSA), 13(7), 2022.
- [3] Vilcapaza Goyzueta, D., Guevara Mamani, J., Sulla Espinoza,E., Supo Colquehuanca, E., Silva Vidal, Y., Pinto, P.P. Evaluation of a NUI Interface for an Explosives Deactivator Robotic Arm to Improve the User Experience. HCI International 2021 Late Breaking Posters. HCII 2021. Communications in Computer and Information Science, vol 1498. Springer, Cham.
- [4] M. A. Andres, L. Pari and S. C. Elvis. Design of a User Interface to Estimate Distance of Moving Explosive Devices with Stereo Cameras. 2021 6th International Conference on Image, Vision and Computing (ICIVC), 2021, pp. 362-366.
- [5] E. Triantafyllidis, C. Mcgreavy, J. Gu and Z. Li, Study ofMultimodal Interfaces and the Improvements on Teleoperation. IEEE Access, vol. 8, pp. 78213-78227, 2020.
- [6] Deborah R. Billings, Kristin E. Schaefer, Jessie Y.C. Chen, and Peter A. Hancock. Human-robot interaction: developing trust in robots. Proceedings of the seventh annual ACM/IEEE international conference on Human-Robot Interaction (HRI 2012). Association for Computing Machinery, New York, NY, USA, 109–110.
- [7] Malabag, Beverly & Santiago Jr, Cereneo & Cahapin, Erwin & Reyes, Jocelyn & Legaspi, Gemma. (2022). Fuzzy Logic Based Size and Ripeness Classification of Banana using Image Processing Technique. International Journal of Emerging Technology and Advanced Engineering. 12. 11-18, 2022.
- [8] Nirunsin, Surasi & Shinonawanik, Praween & Thintawornkul, Tawan &Wongratanaphisan, Theeraphong. Size Estimation of Mango Using Mask-RCNN Object Detection and Stereo Camera for Agricultural Robotics. International Journal of Emerging Technology and Advanced Engineering. 12. 161-168, 2022.
- [9] Wan-Soo Kim, Dae-Hyun Lee, Yong-Joo Kim, Taehyeong Kim, Won-Suk Lee, Chang-Hyun Choi. Stereo-vision-based crop height estimation for agricultural robots. Computers and Electronics in Agriculture. Volume 181,2021.
- [10] M. Pieraccini, G. Luzi and C. Atzeni. Terrain mapping by ground-based interferometric radar IEEE Transactions on Geoscience and Remote Sensing. vol. 39, no. 10, pp. 2176- 2181, Oct. 2001.
- [11] Z. Li, Y. Li, X. Rong and H. Zhang. Grid Map Construction and Terrain Prediction for Quadruped Robot Based on C-Terrain Path. IEEE Access. vol. 8, pp. 56572-56580, 2020.
- [12] B. Zhou et al., A Graph Optimization-Based Indoor Map Construction Method via Crowdsourcing. IEEE Access., vol. 6, pp. 33692-33701, 2018.
- [13] Montoya Angulo, A.; Pari Pinto, L.; Sulla Espinoza, E.; Silva Vidal, Y.; Supo Colquehuanca, E. Assisted Operation of a Robotic Arm Based on Stereo Vision for Positioning near an Explosive Device. MDPI Robotics 2022. 11, 100.
- [14] Yoo, I.-S., & Seo, S.-W. Accurate object distance estimation based on frequency-domain analysis with a stereo camera. IET Intelligent Transport Systems. 11(4), 248–254, 201, 2017
- [15] Adil, E., Mikou, M., Mouhsen, A. novel algorithm for distance measurement using stereo camera. CAAI Trans. Intell. Technol. 7( 2), 177– 186 (2022).
- [16] SOLAK, S., & BOLAT, E. D. A new hybrid stereovisionbased distance-estimation approach for mobile robot platforms. Computers Electrical Engineering., 67, 672–689, 2018.
- [17] A. J. Golkowski, M. Handte, P. Roch and P. J. Marron, Quantifying the Impact of the Physical Setup of Stereo Camera Systems on Distance Estimations. 2020 Fourth IEEE International Conference on Robotic Computing (IRC). 2020, pp. 210-217.
- [18] Setyawan, R. A., Soenoko, R., Mudjirahardjo, P., & Choiron, M. A. Measurement Accuracy Analysis of Distance Between Cameras in Stereo Vision. 2018 Electrical Power, Electronics, Communications, Controls and Informatics Seminar (EECCIS).
- [19] Sanchez-Ferreira, C., Mori, J. Y., Farias, M. C. Q., & Llanos, C. H. A real-time stereo vision system for distance measurement and underwater image restoration. Journal of the Brazilian Society of Mechanical Sciences and Engineering- 38(7), 2039–2049, 2016.
- [20] Budiharto, W., Santoso, A., Purwanto, D., & Jazidie, A. Multiple moving obstacles avoidance of service robot using stereo vision. Telkomnika, 9(3), 433-444, 2012.
- [21] Du, YC., Taryudi, T., Tsai, CT. et al. Eye-to-hand robotictracking and grabbing based on binocular vision. Microsyst Technol 27., 1699–1710 (2021).
- [22] Z. Liang, W.J. Tam, Stereoscopic image generation based ondepth images for 3D TV, IEEE Transactions on Broadcasting, vol. 51, issue: 2, 2005, pp. 191–199.
- [23] A. A. Ahmed, M. K. Elbashir and A. A. Osman, Distance alert system using Stereo vision and feature extraction. International Conference on Communication, Control, Computing and Electronics Engineering., Khartoum, Sudan, 2017, pp. 1-5.
- [24] V. G. Posugade and R. P. Patil, FPGA based design and implementation of disparity estimation for stereo vision system. 2016 International Conference on Computing Communication Control and automation., Pune, India, 2016, pp. 1-5.
- [25] Z. Zhang. A flexible new technique for camera calibration.IEEE Transactions on Pattern Analysis and Machine Intelligence., Nov. 2000, vol. 22, no. 11, pp. 1330-1334.
- [26] J. Zhang, J. Chen, Q. Lin and L. Cheng. Moving Object Distance Estimation Method Based on Target Extraction with a Stereo Camera. IEEE 4th International Conference on Image, Vision and Computing (ICIVC)., Xiamen, China, 2019, pp. 572-577.
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2024).
Typ dokumentu
Bibliografia
Identyfikator YADDA
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