Robotic wheeled vehicle ripple tentacles motion planning method

This paper describes a nonholonomic robotic wheeled vehicle ripple tentacle motion planning method, aiming to improve the vehicle´s trajectory smoothness and avoid frequent weight parameters adjustment in different environments. In the regular tentacle motion planning algorithm, the planning result is selected among the drivable tentacles using a weighted sum cost function. Though the method is simple and easy to understand, it is difficult to adjust the weighted coefficients in different environments. To solve this problem, a geometrical ripple tentacles technique is used to choose a tentacle as a sub-optimal path. Compared with the regular tentacles algorithm, the proposed ripple tentacle algorithm can get a better performance in vehicle´s trajectory smoothness with an acceptable runtime expense. And another two traits can also distinguish this method: (a) it can avoid weight parameter adjustment in different environments and varied vehicle´s states, and (b) it can be used in both unknown environment and partly known environment with goal point and global reference path. In the totally unknown environment, it acts as a pure obstacle avoidance algorithm, and when there is a global path, it can follow the reference path and avoid hazards simultaneously.