distributed formation control

in Dynamic Environments and using Onboard Perception

We develop a fully distributed solution to drive a team of robots to reach a desired formation in the absence of an external positioning system that localizes them. Our solution addresses two fundamental problems that appear in this context. First, we propose a 3-D distributed control law, designed at a kinematic level, that uses two simultaneous consensus controllers: one to control the relative orientations between robots, and another for the relative positions. Second, in order to apply this controller to a group of aerial robots, we combine this idea with a novel sensor fusion algorithm to estimate the relative pose of the robots by using onboard cameras and information from the inertial measurement unit. We validate the distributed algorithm with three quadrotors with downward facing cameras.

We also present a distributed method for formation control with teams of ground/aerial mobile robots navigating in environments with static and dynamic obstacles. Our approach leverages both constrained optimization and multi-robot consensus to compute the parameters of the multi-robot formation in order to 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 within the convex neighborhood of the robots, allowing for reconfiguration if a set of template formations is considered. 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 experiments with four real quadrotors flying in formation in an environment with one moving human.

References

[1] Eduardo Montijano, Eric Cristofalo, Dingjiang Zhou, Mac Schwager, Carlos Sagues. "Vision-based distributed formation control without an external positioning system". IEEE Transactions on Robotics 32 (2), 339 - 351.

[2] Javier Alonso-Mora, Eduardo Montijano, Tobias Nägeli, Otmar Hilliges, Mac Schwager, and Daniela Rus. "Distributed multi-robot formation control in dynamic environments", Autonomous Robots 43 (5), 1079-1100.

[3] Javier Alonso-Mora, Eduardo Montijano, Mac Schwager, Daniela Rus. "Distributed multi-robot formation control among obstacles: A geometric and optimization approach with consensus". 2016 IEEE international conference on robotics and automation (ICRA), 5356-5363.

[4] Eduardo Montijano, Eric Cristofalo, Mac Schwager, Carlos Sagues. "Distributed formation control of non-holonomic robots without a global reference frame". 2016 IEEE International Conference on Robotics and Automation (ICRA), 5248-5254.

[5] Eduardo Montijano, Dingjiang Zhou, Mac Schwager, Carlos Sagüés. "Distributed formation control without a global reference frame" 2014 American Control Conference, 3862-3867.