Journal: Journal of Robotics Research (JRR), Volume:1, Issue:1, Pages: 7-14 Download pdf
Authors: Ata Jahangir Moshayedi, Yibin Xie, Maryam Sharifdoust, Amir Sohail Khan
Date: 7-2024
Abstract: This study aims to enhance the accuracy and efficiency of Omni robots in navigation, reducing errors and resource use to improve safety and task completion in various applications. Utilizing CoppeliaSim (Vrep) for simulation, the research focuses on the Omni robot's performance over homogeneous and non-homogeneous paths using SLAM. Key parameters such as running time, average velocity, body change, and error are analyzed with statistical methods to ensure robust findings. Results show a direct relationship between speed and tracking error, highlighting the need for optimized speed management. The study provides insights into the robot's performance under different conditions, offering valuable data for further optimization. This research contributes to the development of safer, more reliable robotic systems with applications in industrial automation, healthcare, and service robotics. Virtual prototyping reduces development costs and risks, promoting the adoption of advanced robotic technologies and enhancing productivity and safety in various fields.
Keywords: OMNI robot platform, CoppeliaSim, Vrep, Simultaneous Localization and Mapping, SLAM, Levene's Test , Independent samples t-test
References:
[1] Ioan Doroftei, V. Grosu, and Veaceslav Spinu, “Design and Control of an Omni-directional Mobile Robot,” Springer eBooks, pp. 105–110, Aug. 2008, doi: https://doi.org/10.1007/978-1-4020-8737-0_19.
[2] A. Eirale, M. Martini, L. Tagliavini, D. Gandini, M. Chiaberge, and G. Quaglia, “Marvin: an Innovative Omni-Directional Robotic Assistant for Domestic Environments,” Sensors, vol. 22, no. 14, p. 5261, Jul. 2022, doi: https://doi.org/10.3390/s22145261.
[3] C. Prados Sesmero, L. R. Buonocore, and M. Di Castro, “Omnidirectional Robotic Platform for Surveillance of Particle Accelerator Environments with Limited Space Areas,” Applied Sciences, vol. 11, no. 14, p. 6631, Jul. 2021, doi: https://doi.org/10.3390/app11146631.
[4] Ata Jahangir Moshayedi, Atanu Shuvam Roy, L. Liao, Amir Sohail Khan, Amin Kolahdooz, and A. Eftekhari, “Design and Development of Foodiebot Robot: from Simulation to Design,” IEEE access, pp. 1–1, Jan. 2024, doi: https://doi.org/10.1109/access.2024.3355278.
[5] A. Eirale, M. Martini, L. Tagliavini, D. Gandini, M. Chiaberge, and G. Quaglia, “Marvin: an Innovative Omni-Directional Robotic Assistant for Domestic Environments,” Sensors, vol. 22, no. 14, p. 5261, Jul. 2022, doi: https://doi.org/10.3390/s22145261.
[6] Mostafa Mo. Massoud, A. Abdellatif, and Mostafa, “Different Path Planning Techniques for an Indoor Omni-Wheeled Mobile Robot: Experimental Implementation, Comparison and Optimization,” Applied sciences, vol. 12, no. 24, pp. 12951–12951, Dec. 2022, doi: https://doi.org/10.3390/app122412951.
[7] B. Fares, Haïfa Souifi, Mohsen Ghribi, and Yassine Bouslimani, “Omnidirectional Platform for Autonomous Mobile Industrial Robot,” 2021 IEEE 3rd Eurasia Conference on IOT, Communication and Engineering (ECICE), Oct. 2021, doi: https://doi.org/10.1109/ecice52819.2021.9645621.
[8] D. Nister, O. Naroditsky and J. Bergen, "Visual odometry," Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004., Washington, DC, USA, 2004, pp. I-I, doi: 10.1109/CVPR.2004.1315094.
[9] P. Jain, "Odometry and motion planning for omni drive robots," 2014 Innovative Applications of Computational Intelligence on Power, Energy and Controls with their impact on Humanity (CIPECH), Ghaziabad, India, 2014, pp. 164-168, doi: 10.1109/CIPECH.2014.7019080..
[10] P. Li, B. Leng and H. Fu, "Autonomous positioning of omnidirectional mobile robot based on visual inertial navigation," 2020 39th Chinese Control Conference (CCC), Shenyang, China, 2020, pp. 3753-3758, doi: 10.23919/CCC50068.2020.9189018.
[11] Y. Yu, W. Gao, C. Liu, S. Shen and M. Liu, "A GPS-aided Omnidirectional Visual-Inertial State Estimator in Ubiquitous Environments," 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Macau, China, 2019, pp. 7750-7755, doi: 10.1109/IROS40897.2019.8968519.
[12] T. Yokota, K. Watanabe, K. Kobayashi and Y. Kurihara, "Development of visual odometry component by using omni-directional camera," SICE Annual Conference 2011, Tokyo, 2011, pp. 2149-2151.
[13] D. Burschka and G. D. Hager, "V-GPS(SLAM): vision-based inertial system for mobile robots," IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA '04. 2004, New Orleans, LA, USA, 2004, pp. 409-415 Vol.1, doi: 10.1109/ROBOT.2004.1307184.
[14] A. M. Derbas and T. A. Tutunji, "SLAM Algorithm for Omni-Directional Robots based on ANN and EKF," 2023 IEEE Jordan International Joint Conference on Electrical Engineering and Information Technology (JEEIT), Amman, Jordan, 2023, pp. 80-86, doi: 10.1109/JEEIT58638.2023.10185708.
[15] A. S. Kundu, O. Mazumder, A. Dhar, P. K. Lenka, and S. Bhaumik, “Scanning Camera and Augmented Reality Based Localization of Omnidirectional Robot for Indoor Application,” Procedia Computer Science, vol. 105, pp. 27–33, 2017, doi: https://doi.org/10.1016/j.procs.2017.01.183.
[16] Durst, V., Hagel, D., Vander, J., Blaich, M., Bittel, O. (2011). Designing an Omni-Directional Infrared Sensor and Beacon System for the Eurobot Competition. In: Obdržálek, D., Gottscheber, A. (eds) Research and Education in Robotics - EUROBOT 2011. EUROBOT 2011. Communications in Computer and Information Science, vol 161. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21975-7_10
[17] Massoud, M.M.; Abdellatif, A.; Atia, M.R.A. Different Path Planning Techniques for an Indoor Omni-Wheeled Mobile Robot: Experimental Implementation, Comparison and Optimization. Appl. Sci. 2022, 12, 12951. https://doi.org/10.3390/app122412951].
[18] Z. Wang and M. Feng, "Research on Omnidirectional SLAM based on Vehicle-mounted Multi-Camera System," 2021 6th International Symposium on Computer and Information Processing Technology (ISCIPT), Changsha, China, 2021, pp. 798-802, doi: 10.1109/ISCIPT53667.2021.00167
[19] .A. J. Moshayedi, S. M. Zanjani, D. Xu, X. Chen, G. Wang and S. Yang, "Fusion BASED AGV Robot Navigation Solution Comparative Analysis and Vrep Simulation," 2022 8th Iranian Conference on Signal Processing and Intelligent Systems (ICSPIS), Behshahr, Iran, Islamic Republic of, 2022, pp. 1-11, doi: 10.1109/ICSPIS56952.2022.10044044
[20] Azizi, M.R.; Rastegarpanah, A.; Stolkin, R. Motion Planning and Control of an Omnidirectional Mobile Robot in Dynamic Environments. Robotics 2021, 10, 48. https://doi.org/10.3390/robotics10010048
[21]. A. Jahangir Moshayedi, K. S. Reza, A. Sohail Khan, and A. Nawaz, “ Integrating Virtual Reality and Robotic Operation System (ROS) for AGV Navigation”, EAI Endorsed Trans AI Robotics, vol. 2, Apr. 2023.