Path Planning for Nonholonomic Multiple Mobile Robot System with Applications to Robotic Autonomous Luggage Trolley Collection at Airports

In this paper, we propose a novel path planning algorithm for the nonholonomic multiple mobile robot system with applications to a robotic autonomous luggage trolley collection system at airports. We consider this path planning algorithm as a Multiple Traveling Salesman Problem (MTSP). Our path planning algorithm consists of three parts. First, we use the Minimum Spanning Tree (MSP) algorithm to divide the MTSP into a number of independent TSPs, which achieves the task assignment for each mobile robot. Secondly, we implement a closed-loop forward control policy based on the kinematic model of the mobile robot to get a feasible and smooth path. The control cost of the path is used as the new metric in solving the TSPs. Finally, in order to adapt to our case, we modify the TSP as an Open Dynamic Traveling Salesman Problem with Fixed Start (ODTSP-FS) and implement an ant colony algorithm to achieve the path planning for each mobile robot. We evaluate our algorithm with simulation experiments and the experimental results demonstrate that our algorithm can quickly generate feasible and smooth paths for each robot while satisfying the nonholonomic constraints.