Distributed Lloyd-Based Algorithm for Uncertainty-Aware Multi-Robot Under-Canopy Flocking

--In this letter, we present a distributed algorithm for flocking in complex environments that operates at constant altitude, without explicit communication, no a priori information about the environment, and by using only on-board sensing and computation capabilities. We provide sufficient conditions to guarantee that each robot reaches its goal region in a finite time, avoiding collisions with obstacles and other robots without exceeding a desired maximum distance from a predefined set of neighbors (flocking or proximity constraint). The proposed approach allows to operate in crowded scenarios and to deal with tracking errors and on-board sensing errors, without violating safety and proximity constraints. The algorithm was verified through simulations with varying number of UA Vs and also through numerous real-world experiments in a dense forest involving up to four UA Vs. Index T erms--Multi-robot systems, Distributed control, Lloyd-based algorithms. Over the past few decades, numerous applications have emerged for multi-robot systems, exhibiting their undisputed benefits in diverse fields.