Reconfigurable Multi-Robot Formation via Ultra-Wideband Ranging in Unknown Environments

Abstract

This letter presents a reconfigurable leader-follower formation approach using relative pose estimation to steer a robot team to maintain a geometry pattern and pass through narrow spaces in unknown environments. The relative pose is estimated using a nonlinear optimization process and the sliding window approach by minimizing the residual error of short-term peer-to-peer UWB (Ultra-Wideband) ranging and odometry. We enhance the estimation accuracy using pose graph optimization by additionally considering odometry as constraints. To pass through narrow areas in unknown environments, we present a pattern reconfiguration mechanism to determine the formation styles (geometry pattern or linear passing pattern) based on environment traversability. A tracking controller is designed to steer the robots to achieve the desired formation style. The effectiveness and performance of the proposed approach are verified by experiments in an indoor environment with ground nonholonomic robots.