Using a brain-computer interface (BCI) rather than limbs to control multiple robots (i.e., braincontrolled multi-robots) can better assist people with disabilities in daily life than a brain-controlled single robot.For example, one person with disabilities can move by a brain-controlled wheelchair (leader robot) and simultaneously transport objects by follower robots. In this paper, we explore how to control the direction, speed, and formation of a brain-controlled multi-robot system (consisting of leader and follower robots) for the first time and propose a novel multi-robot predictive control framework (MRPCF) that can track users' control intents and ensure the safety of multiple robots. The MRPCF consists of the leader controller, follower controller, and formation planner. We build a whole brain-controlled multi-robot physical system for the first time and test the proposed system through human-in-the-loop actual experiments. The experimental results indicate that the proposed system can track users' direction, speed, and formation control intents when guaranteeing multiple robots' safety. This paper can promote the study of brain-controlled robots and multi-robot systems and provide some novel views into human-machine collaboration and integration.
Brain-controlled robots have important application values in assisting persons with disabilities. However, few studies focus on brain-controlled multiple robots. This paper proposes an assistive controller based on model prediction with the leader-follower formation strategy for developing brain-controlled multiple robots. The controller is composed of a leader controller and a follower controller. The experimental results of brain-controlled multiple robots show that the proposed method can track the user’s lateral and longitudinal control intention and maintain the stability of the multi-robot formation while ensuring the safety of brain-controlled multiple robots. This work can advance the research and development of brain-controlled multiple robots.
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