収縮理論に基づくロボットネットワークの3次元対称フォーメーションの分散アルゴリズム
Decentralized Algorithms for 3D Symmetric Formations in Robotic Networks: a Contraction Theory Approach
巡回追跡と収縮理論を組み合わせ、複数ロボットが3次元空間で正多角形やジョンソン立体などの対称フォーメーションへ大域収束する分散制御則を設計し、クアッドコプター群で実証した。
著者: Sumeet Singh, Edward Schmerling, Marco Pavone
分類: eess.SY, cs.MA, cs.RO, cs.SY
原文アブストラクト
This paper presents decentralized algorithms for formation control of multiple robots in three dimensions. Specifically, we leverage the mathematical properties of cyclic pursuit along with results from contraction and partial contraction theory to design decentralized control algorithms that ensure global convergence to symmetric formations. We first consider regular polygon formations as a base case, and then extend the results to Johnson solid and other polygonal mesh formations. The algorithms are further augmented to allow control over formation size and avoid collisions with other robots in the formation. The robustness properties of the algorithms are assessed in the presence of bounded additive disturbances and their effect on the quality of the formation is quantified. Finally, we present a general methodology for embedding the control laws on complex dynamical systems, in this case, quadcopters, and validate this approach via simulations and experiments on a fleet of quadcopters.
