Staying-alive path planning with energy optimization for mobile robots

Most mobile robots are powered by batteries, and their energy and operation time are limited. Therefore, how to minimize energy consumption and keep mobile robots to stay alive becomes an important problem. In this paper, we propose a staying-alive and energy-efficient path planning algorithm, SLEEP (Staying-aLive and Energy-Efficient Path planning), to solve this problem based on the Tabu-search method. In SLEEP, we consider both energy consumption and staying-alive for the path planning of rechargeable mobile robots. We design and implement our approach based on a real mobile robot platform, and conduct experiments in a real-life environment. The experimental results show that SLEEP can provide an effective path planning by which a robot can be guaranteed to stay alive and finish all tasks with the minimum energy.