Efficient Trajectory Optimization for Robot Motion Planning
This work addresses motion planning for robots, but it appears incremental as it builds on existing optimal control methods with a focus on efficiency.
The paper tackles the challenge of motion planning for multi-jointed robots by presenting an optimal control-based approach that simultaneously addresses path and trajectory planning, with numerical results demonstrating its efficiency and effectiveness.
Motion planning for multi-jointed robots is challenging. Due to the inherent complexity of the problem, most existing works decompose motion planning as easier subproblems. However, because of the inconsistent performance metrics, only sub-optimal solution can be found by decomposition based approaches. This paper presents an optimal control based approach to address the path planning and trajectory planning subproblems simultaneously. Unlike similar works which either ignore robot dynamics or require long computation time, an efficient numerical method for trajectory optimization is presented in this paper for motion planning involving complicated robot dynamics. The efficiency and effectiveness of the proposed approach is shown by numerical results. Experimental results are used to show the feasibility of the presented planning algorithm.