Optimization of global path planning for asymmetric mobile robots
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https://doi.org/10.54939/1859-1043.j.mst.100.2024.46-53Keywords:
AMRs; Asymmetric mobile robots; Global path planning; DWB; SPBL.Abstract
This research focuses on optimizing global path planning for asymmetric mobile robots (AMRs), which are characterized by an asymmetric structure and mobility capabilities commonly encountered in practical applications. The objective is to propose a method for optimizing global trajectory planning, enabling efficient movement of asymmetric AMRs in complex environments, reducing task execution time, and optimizing operational performance. The study employs the SPBL algorithm to search for an optimal path in an environment based on an initial trajectory. The path following process utilizing the Dynamic Window Approach (DWA) is optimized by adjusting cost parameters for basic maneuvers such as straight-line motion, rotations, sliding, and reversing. These parameters are designed to prioritize smooth trajectories while avoiding complex and inefficient maneuvers. The results of the research demonstrate that the proposed method minimizes trajectory complexity, leading to reduced task execution time and improved operational performance of asymmetric AMRs. The findings have potential applications in robotic transport systems in the industrial sector.
References
[1]. Hrbáček, J., T. Ripel, and J. Krejsa. "Ackermann mobile robot chassis with independent rear wheel drives." Proceedings of 14th International Power Electronics and Motion Control Conference EPE-PEMC 2010. IEEE, (2010). DOI: https://doi.org/10.1109/EPEPEMC.2010.5606853
[2]. Wang, C., Liu, X., Yang, X., Hu, F., Jiang, A., & Yang, C. “Trajectory tracking of an omni-directional wheeled mobile robot using a model predictive control strategy”. Applied Sciences, 8(2), 231, (2018). DOI: https://doi.org/10.3390/app8020231
[3]. Tătar, Mihai Olimpiu, et al. "Design and development of an autonomous omni-directional mobile robot with Mecanum wheels." 2014 IEEE International Conference on Automation, Quality and Testing, Robotics. IEEE, (2014). DOI: https://doi.org/10.1109/AQTR.2014.6857869
[4]. V. M. B. D. A. F. A. Filipescu, "Trajectory-tracking and discrete-time sliding-mode control of wheeled mobile robots," 2011. IEEE International Conference on Information and Automation. IEEE, 2011.
[5]. Z. J. Shibing Yu, "Design of the navigation system through the fusion of IMU and wheeled encoders," 2020. Computer Communications 160: 730-737, (2020). DOI: https://doi.org/10.1016/j.comcom.2020.07.009
[6]. Kalman, Rudolph E., and Richard S. Bucy. "New results in linear filtering and prediction theory.": 95-108, (1961). DOI: https://doi.org/10.1115/1.3658902
[7]. Thrun, S.. “Simultaneous localization and mapping. In Robotics and cognitive approaches to spatial mapping”, (pp. 13-41). Berlin, Heidelberg: Springer Berlin Heidelberg, (2008). DOI: https://doi.org/10.1007/978-3-540-75388-9_3
[8]. Thrun, S., & Montemerlo, M. “The graph SLAM algorithm with applications to large-scale mapping of urban structures”. The International Journal of Robotics Research, 25(5-6), 403-429, (2006). DOI: https://doi.org/10.1177/0278364906065387
[9]. Giorgio Grisetti, Cyrill Stachniss, and Wolfram Burgard,“Improved Techniques for Grid Mapping with Rao-Blackwellized Particle Filters”, IEEE Transactions on Robotics, Volume 23, pages 34-46, (2007). DOI: https://doi.org/10.1109/TRO.2006.889486
[10]. Kohlbrecher, S., Meyer, J., Graber, T., Petersen, K., Klingauf, U., & Von Stryk, O.. “Hector open source modules for autonomous mapping and navigation with rescue robots”. In RoboCup 2013: Robot World Cup XVII 17, pp. 624-631. Springer Berlin Heidelberg, (2013). DOI: https://doi.org/10.1007/978-3-662-44468-9_58
[11]. Hess, W., Kohler, D., Rapp, H., & Andor, D. “Real-time loop closure in 2D LIDAR SLAM”. In 2016 IEEE international conference on robotics and automation (ICRA), pp. 1271-1278, (2016). DOI: https://doi.org/10.1109/ICRA.2016.7487258
[12]. Konolige, K., Grisetti, G., Kümmerle, R., Burgard, W., Limketkai, B., & Vincent, R. “Efficient sparse pose adjustment for 2D mapping”. In 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 22-29, (2010). DOI: https://doi.org/10.1109/IROS.2010.5649043
[13]. I. J. Steve Macenski, "SLAM Toolbox: SLAM for the dynamic world", (2021). DOI: https://doi.org/10.21105/joss.02783
[14]. Agarwal, S., Mierle, K., & Others. (n.d.). Ceres solver. http://ceres-solver.org
[15]. Likhachev, Maxim. "Search-Based Planning Library (SBPL)." (2016).
[16]. Limpert, Nicolas, Stefan Schiffer, and Alexander Ferrein. "A local planner for Ackermann-driven vehicles in ROS SBPL." 2015. Pattern Recognition Association of South Africa and Robotics and Mechatronics International Conference (PRASA-RobMech). IEEE, (2015). DOI: https://doi.org/10.1109/RoboMech.2015.7359518
[17]. A. &. R. L. L. d. I. A. e. R. d. P. d. Milano, "Implementation, comparison, and advances in global planners using Ackerman motion primitives," (2018).
[18]. ROS, "sbpl_lattice_planner," [Online]. Available: https://wiki.ros.org/sbpl_lattice_planner.
[19]. Fox, D., Burgard, W., & Thrun, S. “The dynamic window approach to collision avoidance”. IEEE Robotics & Automation Magazine, 4(1), 23-33, (1997). DOI: https://doi.org/10.1109/100.580977