A New Optimization-Based Method for Motion Planning in Dynamic Environments
Jing Ren, Kenneth A. Mcisaac, Xishi Huang · 2005
In this paper, we present a new optimization based motion planning method for dynamic environments. Compared with the optimization method proposed in Esposito [1], our optimization method based on modified Newton’s method can greatly improve the performance with very modest computation effort. To illustrate our techniques, we consider a robot team motion planning problem in a complex “maze” with obstacles of arbitrary shape. Simulation results show that robots with the new optimization method can reach the goal faster with much smoother trajectory. Finally we proved the proposed control law is stable at all times.