Searching Energy-Efficient Route in Rough Terrain for Mobile Robot with Ant Algorithm

Abstract

Recently, the ant algorithm has been widely used to solve the problem for searching optimized route from various different paths. It can be applied for searching an appropriate route that consumes less energy in mobile robot area as well. However, the previous optimized routes resulting from the ant algorithms considered only in flat terrain environment. They did not mention rough terrain environment. For the rough terrain, the optimized results might not be optimized in term of energy, due to slopes contained inside. This paper presents the application of ant algorithms for searching energy-efficient route of mobile robot in the rough terrain environment. The conventional ant colony optimization (ACO) algorithm and the adapted ACO algorithm are used to find the optimized routes in terms of distance and energy for comparison. The experimental results showed that, by using the speed with distance weighting factor, the adapted ACO yielded the optimized distance and energy in the flat terrain. In the rough terrain, the adapted ACO could also provide the energy-efficient routes better than the flat terrain. However, it could not be comparable with the ACO in some case and is required further improvement.