Print Email Facebook Twitter Distributed multi-robot formation control in dynamic environments Title Distributed multi-robot formation control in dynamic environments Author Alonso-Mora, J. (TU Delft Learning & Autonomous Control) Montijano, Eduardo (Universidad de Zaragoza) Nägeli, Tobias (ETH Zürich) Hilliges, Otmar (ETH Zürich) Schwager, Mac (Stanford University) Rus, Daniela (Massachusetts Institute of Technology) Date 2018 Abstract This paper presents a distributed method for formation control of a homogeneous team of aerial or ground mobile robots navigating in environments with static and dynamic obstacles. Each robot in the team has a finite communication and visibility radius and shares information with its neighbors to coordinate. Our approach leverages both constrained optimization and multi-robot consensus to compute the parameters of the multi-robot formation. This ensures that the robots make progress and avoid collisions with static and moving obstacles. In particular, via distributed consensus, the robots compute (a) the convex hull of the robot positions, (b) the desired direction of movement and (c) a large convex region embedded in the four dimensional position-time free space. The robots then compute, via sequential convex programming, the locally optimal parameters for the formation to remain within the convex neighborhood of the robots. The method allows for reconfiguration. Each robot then navigates towards its assigned position in the target collision-free formation via an individual controller that accounts for its dynamics. This approach is efficient and scalable with the number of robots. We present an extensive evaluation of the communication requirements and verify the method in simulations with up to sixteen quadrotors. Lastly, we present experiments with four real quadrotors flying in formation in an environment with one moving human. Subject Collision avoidanceDistributed roboticsDronesDynamic environmentsFormation controlMicro air vehiclesMulti-robot systemsUnmanned aerial vehicles To reference this document use: http://resolver.tudelft.nl/uuid:80114cfb-9065-4a02-894c-8ddf3f52c5a2 DOI https://doi.org/10.1007/s10514-018-9783-9 ISSN 0929-5593 Source Autonomous Robots, 43 (2019) (5), 1079-1100 Part of collection Institutional Repository Document type journal article Rights © 2018 J. Alonso-Mora, Eduardo Montijano, Tobias Nägeli, Otmar Hilliges, Mac Schwager, Daniela Rus Files PDF Alonso_Mora2018_Article_D ... rmatio.pdf 3.5 MB Close viewer /islandora/object/uuid:80114cfb-9065-4a02-894c-8ddf3f52c5a2/datastream/OBJ/view