An application of ant algorithm for searching energy-efficient route a mobile robot takes using energy as a weighting factor

Abstract

A problem related to energy consumption of a mobile robot involves finding out what route the robot can take that uses the least energy. An ant colony optimization algorithm (ACO) can solve this problem. However, it is applicable only for route on a flat terrain. This paper proposes an adapted ant colony optimization (adapted ACO) algorithm that is applicable for route on a rough terrain as well. This adaptation introduces a weight that is the energy expended on a route that may have upward slopes, downward slopes, and flat surfaces. Experiments were conducted to test the algorithm. The experimental results show that our adapted ACO did successfully find a route that expended the least energy, though it was not the shortest one. We also found the following interesting facts: an energy-efficient route has more downward slopes than upward ones; the energy expended increases with the steepness of the slopes along a route; and the energy expended is likely to be lower if the robot’s velocity is not constrained to be constant throughout the route.