Experiments on the control of differential game of target defense

This paper evaluates experimentally a novel strategy for solving a variant of the differential game of target defense in the presence of obstacles. The state-of-the-art approaches mostly employ an offline optimization strategy that is only applicable to holonomic systems. This paper presents an online optimization technique, by designing a trade-off parameter that integrates game theory with the model predictive control which allows a nonholonomic defender to intercept an attacker while simultaneously defending a specific target. Several indoor laboratory experiments validate the performance of the proposed approach and compared with a standard model predictive control approach.