Chase and Track: Toward Safe and Smooth Trajectory Planning for Robotic Navigation in Dynamic Environments

• Published in: IEEE transactions on industrial electronics (1982) 2023-01, Vol.70 (1), p.604-613
• Main Authors: Wang, Chaoqun, Chen, Xiangyu, Li, Chenming, Song, Rui, Li, Yibin, Meng, Max Q.-H.
• Format: Article
• Language: English
• Subjects: Adaptive horizon model predictive control (MPC); autonomous navigation; Dynamics; motion planning; Navigation; Path planning; Planning; Predictive control; Robot dynamics; Robots; Shortest path planning; Tracks (paths); Trajectory; Trajectory planning; Vehicle dynamics
• ISSN: 0278-0046; 1557-9948
• DOI: 10.1109/TIE.2022.3148753

In this article presents a trajectory planning approach toward safe and smooth robot motion in dynamic environments. We develop a hierarchical planning framework with a global planner generating the shortest path between the robot and the navigation target. Specially, a virtual target (VT) is set to run on the global path with a designed velocity. At the local level, the robot chases the VT and tracks the global path when traveling through the dynamic environment. We employ the model predictive control (MPC) framework for the local path generation. In particular, the prediction horizon of the MPC is adaptively changed concerning the distance between the robot and the VT. It implicitly reflects the crowdedness of the environment, which helps reduce the environmental uncertainty. Besides, we develop an event-triggered mechanism that executes the local plan aperiodically to release the computational burden. Based on the local chasing and tracking performance, we develop a global path replanning scheme in response to the untraversable area emerging in the dense environment. The developed framework is validated through extensive experiments in dynamic environments, demonstrating that the robot can reach the target faster and showcase a safer and smoother trajectory in the navigation.