Segregation of Multiple Robots Using Model Predictive Control With Asynchronous Path Smoothing

Abstract

Segregation is an essential requirement for a multi-robot system performing collaborative tasks in different groups. This paper proposes a collision-free framework to segregate multiple robots in the presence of any disturbance in motion, causing an asynchronous event. For this, a Model Predictive Control (MPC) law is developed, introducing a novel cost function that segregates multiple robots sharing common properties in different groups. An Asynchronous Path Smoothing (APS) strategy is integrated within the MPC framework to ensure the smooth motion profile of robots having uncertainty in their states due to external disturbances. The on-demand collision avoidance is incorporated to avoid inter-robot collisions. Simulations and hardware experiments are presented using a system of five robots to verify and substantiate the proposed framework.