Comparison of Optimization Methods to Minimize the Overlapped Path in Coverage Path Planning for Underwater Mining Robot

Abstract

Nowadays, there are several optimization methods which have been documented and explained individually in detail such as genetic algorithm, ant colony algorithm, and simulated annealing algorithm. However, there is still a lack of comparative analysis of these algorithms and their applications to minimize the overlapped path in coverage path planning. This paper proposes comparison of optimization methods to minimize the overlapped path in coverage path planning for an underwater mining robot. To do this task, firstly, the high slope regions are detected and treated as obstacle. Secondly, Morse cell decomposition method is applied to divided the whole area into smaller areas based on the obstacles positions. Finally, the genetic algorithm, ant colony algorithm, and simulated annealing algorithm are used to generate the coverage sequence to minimize the overlapped path. The emphasis of this comparison is on the computation time of generating a trajectory, length of overlapped path and the shortest distance of the generated trajectory. The simulations are done to show the effectiveness of each optimization method.