Path Planning for Mobile Robots Based on Continuous Dynamic Movement Primitives

Aiming at the problem of mobile robot path planning in two-dimensional dynamic scenes, we propose a novel path-planning method, called continuous dynamic movement primitives(CDMPs). The method is an extension of the traditional dynamic movement primitives. By learning the motion trajectory of the demonstration, we obtain the weight sequence of each movement primitive. We can track unknown dynamic targets by updating the phase variables. The method overcomes the dependence of mobile robots on the environment model and solves the path-planning problem of tracking moving targets and avoiding dynamic obstacles in dynamic scenes. Finally, through a series of simulation experiments, the feasibility of the algorithm is verified. The simulation results show that the CDMPs algorithm has better continuous performance and planning efficiency than the traditional DMPs method for mobile robot path planning in dynamic scenes.