Control design for collaborative object transportation using pairs of differential-drive robots via control barrier functions

Abstract

This paper presents a control design framework for collaborative object transportation using differential-drive robots. Specifically, pairs of robots are required to navigate toward a target pose while maintaining predefined inter-robot distances and relative orientations, as well as avoiding collisions with unknown static obstacles and other robot groups. To achieve this, both centralized and distributed quadratic programming (QP)-based controllers are developed, where control barrier functions (CBFs) are incorporated as constraints to handle multiple control objectives simultaneously. The performance of the proposed controllers is evaluated in both simulations and real-world experiment through various scenarios, including navigation in complex, office-like environments.