Trust-based leader selection for bilateral haptic teleoperation of multi-robot systems

Abstract

Multi-robot teleoperation systems benefit from human's capabilities in adaptation to new environments and decision-making in the presence of uncertainty and complexity. In these applications, usually a human operator determines the general behaviour of the multi-robot team via selecting and controlling a leader robot while the follower robots coordinate with the team autonomously. Trust is a major factor in human's allocation of autonomy among the team of robots. A trust-based online leader selection strategy is proposed in this work for multi-robot bilateral haptic teleoperation with applications in collective position tracking and synchronization. Human-to-robot trust is computed and utilized as a dynamic criterion to select the leader. Also, robot-to-human trust is used to dynamically scale the haptic force feedback cues so that the operator receives smaller force feedback when his/her performance in leading the team is higher. This reduces the physical workload of the operator. Due to the trust-based leader switching and force feedback scaling, the stability of the closed-loop system may be lost. We guarantee this stability via passivity-based techniques. Finally, our experimental results indicate that the trust-based leader selection strategy can reduce task completion time by 35.25% and formation error by 41.64% compared to a non-leader switching strategy.