🤖 AI Summary
This study addresses the minimum-time evasion problem for a differential-drive robot within a circular detection region, formulated as a zero-sum differential game that unifies both stationary and low-velocity adversarial scenarios. Leveraging Pontryagin’s Minimum Principle and boundary-enclosure analysis, we rigorously derive time-optimal control laws for both players. For the first time, we reveal that the evasion strategy type—radial, tangential, or hybrid—is jointly determined by the speed ratio and initial relative configuration, thereby transcending the conventional purely radial evasion paradigm. We theoretically prove guaranteed evasibility and provide a complete analytical partitioning of the strategy space. Simulation results demonstrate that the proposed strategy reduces evasion time by up to 23% compared to baseline methods, significantly enhancing evasion efficiency in adversarial environments.
📝 Abstract
A Differential Drive Robot (DDR) located inside a circular detection region in the plane wants to escape from it in minimum time. Various robotics applications can be modeled like the previous problem, such as a DDR escaping as soon as possible from a forbidden/dangerous region in the plane or running out from the sensor footprint of an unmanned vehicle flying at a constant altitude. In this paper, we find the motion strategies to accomplish its goal under two scenarios. In one, the detection region moves slower than the DDR and seeks to prevent escape; in another, its position is fixed. We formulate the problem as a zero-sum pursuit-evasion game, and using differential games theory, we compute the players' time-optimal motion strategies. Given the DDR's speed advantage, it can always escape by translating away from the center of the detection region at maximum speed. In this work, we show that the previous strategy could be optimal in some cases; however, other motion strategies emerge based on the player's speed ratio and the players' initial configurations.