Energy-Aware Planning of Heterogeneous Multi-Agent Systems for Serving Cooperative Tasks with Temporal Logic Specifications

We address a coordination problem for a team of heterogeneous and energy-limited agents to achieve cooperative tasks given as team-level spatio-temporal specifications. We assume that agents have stochastic energy dynamics and do not have identical capabilities. We define the team-level specification using Signal Temporal Logic (STL) with integral predicates, which can express tasks that can be completed collectively in an asynchronous way. We first abstract the environment as a graph using sampling-based methods. This abstraction includes the possible paths of different types of agents and ensures the availability of recharging within a certain distance. Then, we formulate a mixed-integer program over this abstraction to find the high-level paths of the agents. Finally, we steer the agents in the environment according to the nominal plan under stochastic energy consumption models and a recharging policy. Such stochastic energy dynamics cause deviations from the nominal plan and delays in completing the tasks. Accordingly, we define and evaluate the expected delay (temporal relaxation) in achieving the STL specification under the proposed solution.