Active-sensing-based decentralized control of autonomous mobile agents for quick and smooth collision avoidance

There is an increasing demand for multi-agent systems in which each mobile agent, such as a robot in a warehouse or a flying drone, moves toward its destination while avoiding other agents. Although several control schemes for collision avoidance have been proposed, they cannot achieve quick and safe movement with minimal acceleration and deceleration. To address this, we developed a decentralized control scheme that involves modifying the social force model, a model of pedestrian dynamics, and successfully realized quick, smooth, and safe movement. However, each agent had to observe many nearby agents and predict their future motion; that is, unnecessary sensing and calculations were required for each agent. In this study, we addressed this issue by introducing active sensing. In this control scheme, an index referred to as the "collision risk level" is defined, and the observation range of each agent is actively controlled on this basis. Through simulations, we demonstrated that the proposed control scheme works reasonably while reducing unnecessary sensing and calculations.