Divide and conquer evolutionary TSP solution for vehicle path planning

Abstract

The problem of robotic area coverage is applicable to many domains, such as search, agriculture, cleaning, and machine tooling. The robotic area coverage task is concerned with moving a vehicle with an effector, or sensor, through the task space such that the sensor passes over every point in the space. For covering complex areas, back and forth paths are inadequate. This paper presents a real-time path planning architecture consisting of layers of a clustering method to divide and conquer the problem combined with a two layered, global and local optimization method. This architecture is able to optimize the execution of a series of waypoints for a restricted mobility vehicle, a fixed wing airplane.