Implementation of the Multiple Tasks Allocation Problem for Mobile Robots

Abstract

The article researches path planning of the multiple task allocation problems using searching algorithms for multiple mobile robots, and solves the shortest path problems such that mobile robots can move from multiple start points to reach all task points in a collision-free space. The searching algorithms contain auction algorithm, greedy algorithm and 2-opt exchange heuristic algorithm. In this manner, the supervised computer constructs the motion paths using sequential single-item auction algorithm to search all task points for multiple mobile robots, and use greedy algorithm and 2-opt exchange heuristic algorithm to improve the shortest paths from the previous motion paths. That is to say, the total displacement of the multiple mobile robots is minimal. The supervised computer controls the mobile robots searching all task points from multiple start points through the other points via wireless RF interface. We develop the user interface to help users filling the position data of the mobile robots and all task points, and program the motion paths of multiple mobile robots using the proposed algorithms. It can display the previous motion path and the improving motion paths of mobile robots on real-time using the proposed algorithms. The simulated results present that the proposed algorithms can find the shortest motion paths for mobile robots moving to all task points from multiple start points in a collision-free space. Finally, we implement the experiment scenario using the four module-based mobile robots that move on the motion platform according to the programmed motion paths.