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.
Highlights
In this paper we present a method for formation control that is ideally suited for these kind of flexible multirobot formations, since our approach is capable of adjusting several parameters of the formation dynamically to avoid collisions with the environment
We present a holistic method where we rely on convex optimization techniques to compute a convex region in free position-time space and on non-convex optimization techniques to compute the configuration for the team of robots
If the human walks in the environment or runs with constant speed, the formation control method updates the parameters of the formation to successfully avoid the moving person
Summary
Multi-robot systems will be ubiquitous to perform many tasks, such as surveillance (Schwager et al 2011), inspection (Suzuki et al 2000), factory automation (Alonso-Mora et al 2015a), logistics (Wurman et al 2008) or cinematography (Nägeli et al 2017b) While some of these problems require team navigation in a rigid pattern, other scenarios, such as cooperative manipulation of deformable objects or transportation of cable-suspended loads, allow for more flexibility, yet requiring certain level of coordination. This is the case, for example, for a team of robots that fly through narrow canyons while preserving inter-robot communication
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