Robust trajectory tracking and obstacle avoidance control for omnidirectional mobile robots.
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| Title: | Robust trajectory tracking and obstacle avoidance control for omnidirectional mobile robots. |
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| Authors: | Huang, He1 (AUTHOR), Liu, Haibin1 (AUTHOR) liuhb@bjut.edu.cn, Li, Mingfei1 (AUTHOR), Ren, Fujie1 (AUTHOR), Xia, Minghao2 (AUTHOR) |
| Source: | Asian Journal of Control. May2026, Vol. 28 Issue 3, p1187-1198. 12p. |
| Subjects: | Obstacle avoidance (Robotics), Robotic trajectory control, Robust control, Predictive control systems, Mobile robots, Potential field method (Robotics), Autonomous robots |
| Abstract: | In environments with obstacles and uncertain disturbances, ensuring safe and robust control is critical for the reliable operation of autonomous robots. This paper presents a robust hierarchical control strategy based on nonlinear model predictive control (NMPC) to address these challenges. The strategy enables safe motion control of omnidirectional mobile robot (OMR) in complex environments. In the upper‐level planning module, the artificial potential field (APF) is incorporated into the NMPC objective function to generate collision‐free reference trajectories. The lower‐level tracking module computes the optimal nominal control and employs a tube‐based model predictive control (MPC) feedback strategy to enhance robustness against disturbances. Simulation results confirm that the proposed approach successfully plans safe obstacle‐avoiding trajectories while achieving high precision and robust trajectory tracking. [ABSTRACT FROM AUTHOR] |
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| Database: | Engineering Source |
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| Abstract: | In environments with obstacles and uncertain disturbances, ensuring safe and robust control is critical for the reliable operation of autonomous robots. This paper presents a robust hierarchical control strategy based on nonlinear model predictive control (NMPC) to address these challenges. The strategy enables safe motion control of omnidirectional mobile robot (OMR) in complex environments. In the upper‐level planning module, the artificial potential field (APF) is incorporated into the NMPC objective function to generate collision‐free reference trajectories. The lower‐level tracking module computes the optimal nominal control and employs a tube‐based model predictive control (MPC) feedback strategy to enhance robustness against disturbances. Simulation results confirm that the proposed approach successfully plans safe obstacle‐avoiding trajectories while achieving high precision and robust trajectory tracking. [ABSTRACT FROM AUTHOR] |
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| ISSN: | 15618625 |
| DOI: | 10.1002/asjc.3726 |
