Collaborative Mission Planning for Long-Term Operation Considering Energy Limitations

Abstract

Mobile robotics research and deployment is highly challenged by energy limitations, particularly in marine robotics applications. This challenge can be addressed by autonomous transfer and sharing of energy in addition to effective mission planning. Specifically, it is possible to overcome energy limitations in robotic missions using an optimization approach that can generate trajectories for both working robots and mobile chargers while adapting to environmental changes. Such a method must simultaneously optimize all trajectories in the robotic network to be able to maximize overall system efficiency. This letter presents a Genetic Algorithm based approach that is capable of solving this problem at a variety of scales, both in terms of the size of the mission area and the number of robots. The algorithm is capable of re-planning during operation, allowing for the mission to adapt to changing conditions and disturbances. The proposed approach has been validated in multiple simulation scenarios. Field experiments using an autonomous underwater vehicle and a surface vehicle verify feasibility of the generated trajectories. The simulation and experimental validation show that the approach efficiently generates feasible trajectories to minimize energy use when operating multi-robot networks.