Searching optimization route by using Pareto solution with ant algorithm for mobile robot in rough terrain environment

Abstract

A problem related to searching routes of a mobile robot involves finding the route that has the shortest distance and consumes the least energy, or an energy-efficient route. An ant colony optimization (ACO) algorithm can be used to solve this problem, but only on a flat terrain, since energy is depended on the distance. The adapted ACO can also be applied for searching the energy-efficient routes in the rough terrain, but it is difficult to achieve both criteria, simultaneously. In the rough terrain, the least energy route might not have the shortest distance. Also, the route having the shortest distance might not consume the least energy. In this scenario, an optimized route is required. This paper proposes a method to find the optimized route of a mobile robot in terms of energy and distance on the rough terrain by using a Pareto solution with adapted ACO algorithm. In the proposed method, the adapted ACO is applied for searching a set of routes that consumes the least energy. Then, the Pareto solution is deployed to find the optimized route in terms of energy and distance. The experiment was conducted by simulation to verify the proposed searching method. The experimental result shows that the optimized route having appropriate energy and distance can be found. It can be implied that this optimized route is the energy-efficient route in rough terrain environment.