On the Adequacy of Tabu Search for Global Robot Path Planning Problem in Grid Environments

This paper investigates the capabilities of tabu search for solving the global path planning problem in grid maps. Accordingly, a tabu search system model is designed and a tabu search planner algorithm for solving the path planning problem is proposed. A comprehensive simulation study is conducted using the proposed model and algorithm, in terms of solution quality and execution time. A comparison between our results with those of A* and genetic algorithms (GA) is presented for small, medium and large-scale grid maps. Simulation results show that the tabu search planner is able to find the optimal solution for small scale environments. However, for large scale maps, it provides near-optimal solutions with small gap while ensuring shorter execution times as compared to the A* Algorithm. A discussion about the advantages and limitations of TS for solving a path planning problem is also presented.