Co-design of Control and Planning for Multi-rotor UAVs with Signal Temporal Logic Specifications
This work addresses the challenge of ensuring safe and efficient urban air mobility missions for UAV operators and planners, though it appears incremental as it builds on existing trajectory generation methods.
The paper tackles the problem of planning and controlling multi-rotor UAVs with complex Signal Temporal Logic (STL) specifications, which is computationally intensive and often leads to infeasible trajectories or limited control capabilities, by presenting a co-design approach that ensures dynamically feasible trajectories with bounded tracking error, as demonstrated through simulations.
Urban Air Mobility (UAM), or the scenario where multiple manned and Unmanned Aerial Vehicles (UAVs) carry out various tasks over urban airspaces, is a transportation concept of the future that is gaining prominence. UAM missions with complex spatial, temporal and reactive requirements can be succinctly represented using Signal Temporal Logic (STL), a behavioral specification language. However, planning and control of systems with STL specifications is computationally intensive, usually resulting in planning approaches that do not guarantee dynamical feasibility, or control approaches that cannot handle complex STL specifications. Here, we present an approach to co-design the planner and control such that a given STL specification (possibly over multiple UAVs) is satisfied with trajectories that are dynamically feasible and our controller can track them with a bounded tracking-error that the planner accounts for. The tracking controller is formulated for the non-linear dynamics of the individual UAVs, and the tracking error bound is computed for this controller when the trajectories satisfy some kinematic constraints. We also augment an existing multi-UAV STL-based trajectory generator in order to generate trajectories that satisfy such constraints. We show that this co-design allows for trajectories that satisfy a given STL specification, and are also dynamically feasible in the sense that they can be tracked with bounded error. The applicability of this approach is demonstrated through simulations of multi-UAV missions.