Decentralized Motion Planning with Collision Avoidance for a Team of UAVs under High Level Goals

TL;DR

This paper presents a hybrid control strategy for decentralized UAV teams that ensures collision avoidance and goal achievement using formal verification and 3D bounding spheres, validated through simulations and experiments.

Contribution

It introduces a novel hybrid control approach combining formal methods and decentralized navigation for UAVs with collision avoidance under high-level goals.

Findings

Control laws successfully navigate UAVs among regions of interest.

Method guarantees collision avoidance and goal satisfaction.

Validated through simulations and real quadrotor experiments.

Abstract

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.