Decentralized Motion Planning with Collision Avoidance for a Team of UAVs under High Level Goals
This addresses motion planning for UAV teams, but it is incremental as it extends previous work on decentralized navigation functions.
The paper tackles motion planning for teams of UAVs with high-level goals by proposing a hybrid control strategy that guarantees local goal accomplishment using temporal logic formulas while ensuring inter-agent collision avoidance through 3-D bounding spheres and decentralized navigation functions. Simulation and experimental results with quadrotors verify the method's validity.
This paper addresses the motion planning problem for a team of aerial agents under high level goals. We propose a hybrid control strategy that guarantees the accomplishment of each agent's local goal specification, which is given as a temporal logic formula, while guaranteeing inter-agent collision avoidance. In particular, by defining 3-D spheres that bound the agents' volume, we extend previous work on decentralized navigation functions and propose control laws that navigate the agents among predefined regions of interest of the workspace while avoiding collision with each other. This allows us to abstract the motion of the agents as finite transition systems and, by employing standard formal verification techniques, to derive a high-level control algorithm that satisfies the agents' specifications. Simulation and experimental results with quadrotors verify the validity of the proposed method.