Robust Distributed Planar Formation Control for Higher-Order Holonomic and Nonholonomic Agents

TL;DR

This paper introduces a fully distributed formation control method for various agent dynamics that does not rely on global positioning, enabling robust and collision-free formation achievement with experimental validation.

Contribution

It extends barycentric-coordinate-based control to higher-order and nonholonomic agents, ensuring robustness and enabling distributed collision avoidance without global information.

Findings

Successfully extended BCB control to complex agent dynamics.

Proved robustness to input saturation and unmodeled actuator dynamics.

Validated approach through simulations and real-world experiments.

Abstract

We present a distributed formation control strategy for agents with a variety of dynamics to achieve a desired planar formation. Our approach is based on the barycentric-coordinate-based (BCB) control, which is fully distributed, does not require inter-agent communication or a common sense of orientation, and can be implemented using relative position measurements acquired by agents in their local coordinate frames. This removes the need for global positioning or alignment of local coordinate frames, which are required across several existing strategies. We show how the BCB control for agents with the simplest dynamical model, i.e., the single-integrator dynamics, can be extended to agents with higher-order dynamics such as quadrotors, and nonholonomic agents such as unicycles and cars. Specifically, our extension preserves the desired convergence and robustness guarantees of the BCB approach and is provably robust to saturations in the input and unmodeled linear actuator dynamics for unicycle and car agents. We further show that under our proposed BCB control design, the agents can move along a rotated and scaled control direction without affecting the convergence to the desired formation. This observation is used to design a fully distributed collision avoidance strategy, which is often not considered in the formation control literature. We demonstrate the proposed approach in simulations and further present a distributed robotic platform to test the strategy experimentally. Our experimental platform consists of off-the-shelf equipment that can be used to test and validate other multi-agent algorithms. The code and implementation instructions for this platform are available online.