Multi-UAV Deployment in Obstacle-Cluttered Environments with LOS Connectivity

TL;DR

This paper presents a novel multi-UAV deployment method in obstacle-rich environments, ensuring LOS connectivity and collision avoidance through a minimum-edge RRT* topology and a distributed MPC strategy, validated by simulations and hardware tests.

Contribution

It introduces an efficient topology design and a real-time motion control strategy that guarantees LOS connectivity and collision-free trajectories for multi-UAV systems in complex environments.

Findings

Guaranteed collision-free trajectories with LOS connectivity.

Effective deployment topology requiring fewer UAVs.

Successful validation through simulations and hardware experiments.

Abstract

A reliable communication network is essential for multiple UAVs operating within obstacle-cluttered environments, where limited communication due to obstructions often occurs. A common solution is to deploy intermediate UAVs to relay information via a multi-hop network, which introduces two challenges: (i) how to design the structure of multi-hop networks; and (ii) how to maintain connectivity during collaborative motion. To this end, this work first proposes an efficient constrained search method based on the minimum-edge RRT$^\star$ algorithm, to find a spanning-tree topology that requires a less number of UAVs for the deployment task. To achieve this deployment, a distributed model predictive control strategy is proposed for the online motion coordination. It explicitly incorporates not only the inter-UAV and UAV-obstacle distance constraints, but also the line-of-sight (LOS) connectivity constraint. These constraints are well-known to be nonlinear and often tackled by various approximations. In contrast, this work provides a theoretical guarantee that all agent trajectories are ensured to be collision-free with a team-wise LOS connectivity at all time. Numerous simulations are performed in 3D valley-like environments, while hardware experiments validate its dynamic adaptation when the deployment position changes online.