A Decentralized and Adaptive Flocking Algorithm for Autonomous Mobile Robots

Abstract

Recently, flocking of a group of mobile robots is gained a lot of attentions due to its wide applications, such as manufacturing, surveillance and space exploration. It is necessary for all robots to adapt to the complex environment during flocking. In this paper, we propose a decentralized flocking algorithm, which can avoid collision between a robot and its neighbors and the collision between robots and obstacles when there are obstacles in the environment. By simulation results, we find this algorithm can effectively achieve the goal of collision avoidance.

The Null-Space-Based Behavioral Control for Swarm Unmanned Aerial Vehicles

“…Each UAV describe the individual maneuvers based on its neighbors. Collision Avoidance and Flock Centering can be combined to a behavior named neighbor behavior which can keep desired distance from neighbors when there are no obstacles [12].…”

An artifical physics-based 3D swarm control strategy

“…There is vast research in literature on the swarm flocking behavior, motivated from various fields including artificial physics to social animal behavior (see for instance [6], [7], [8], [9], [10]). However, most of these studies do not consider the local formation between members of swarm.…”

A Customized Flocking Algorithm for Swarms of Sensors Tracking a Swarm of Targets

“…In [7], Yan, Naixue, Nak Young, et. al have discussed a decentralized and adaptive flocking algorithm for autonomous mobile robots.…”