Energy-Aware Coordination of Heterogeneous Robotic Systems with Mobile Charging Stations for Long-Term Environmental Monitoring

This paper presents an optimization-based control framework for energy-aware control of a heterogeneous robotic system deployed for long-term environmental monitoring applications. The robotic system is comprised of a mobile charging station controlled to provide the required energy resources to a robot whose tasks have to be executed continuously and persistently. The charging station is assumed to be able to harvest energy from the environment (e.g. via solar panels) and is controlled to maximize the collected energy. We propose suitable models for the energy dynamics of both robots, as well as models for the environment dynamics. The energy sufficiency of the heterogeneous robotic system is translated into the forward invariance of a subset of the system state space and turned into a control input constraint by leveraging Control Barrier Functions (CBFs). The resulting control algorithm is a convex optimization problem that is solved online. The feasibility of the optimization problem is analyzed and sufficient conditions to ensure it are provided in terms of model parameters. The effectiveness of the controlled system at ensuring energy awareness is validated both in simulation as well as on real robotic platforms.