Dynamic Simulation Benchmark for Motion Coordination Tasks

Existing motion coordination simulation environ-ments can only support a limited number of preset scenarios and lack the capability to simulate complex dynamic environments, which hinders the fulfillment of practical needs and restricts the generalization ability and training effectiveness of algorithms. This paper proposes an innovative simulation environment that supports the simulation of complex dynamic environments and offers flexible configuration. It can dynamically adjust to meet different testing requirements, thereby enhancing the general-ization ability and training speed of algorithms while main-taining sufficient environmental complexity to ensure training effectiveness. Experimental results show that the new simulation environment performs excellently in complex dynamic scenarios, significantly improving the generalization ability and training efficiency of algorithms. This provides a more reliable and efficient solution for the training and validation of algorithms for motion coordination tasks.