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Optimization-Based Distributed Flocking Control for Multiple Rigid Bodies

Tatsuya Ibuki, Sean Wilson, Junya Yamauchi, Masayuki Fujita, Magnus Egerstedt

2020IEEE Robotics and Automation Letters54 citationsDOI

Abstract

This letter considers distributed flocking control on the Special Euclidean group for networked rigid bodies. The method captures the three flocking rules proposed by Reynolds: cohesion; alignment; and separation. The proposed controller is based only on relative pose (position and attitude) information with respect to neighboring rigid bodies so that it can be implemented in a fully distributed manner using only local sensors. The flocking algorithm is moreover based on pose synchronization methods for the cohesion/alignment rules and achieves safe separation distances through the application of control barrier functions. The control input for each rigid body is chosen by solving a distributed optimization problem with constraints for pose synchronization and collision avoidance. Here, the inherent conflict between cohesion and separation is explicitly handled by relaxing the position synchronization constraint. The effectiveness of the proposed flocking algorithm is demonstrated via simulation and hardware experiments.

Topics & Concepts

Flocking (texture)Computer scienceControl theory (sociology)Distributed computingEuclidean groupCohesion (chemistry)Artificial intelligenceMathematicsControl (management)Affine transformationAffine spaceMaterials scienceChemistryPure mathematicsComposite materialOrganic chemistryDistributed Control Multi-Agent SystemsAdvanced Memory and Neural ComputingModular Robots and Swarm Intelligence
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