Rescue robots can perform rescue missions in dangerous and complex environments, protect humans from harm, and improve the efficiency and effectiveness of rescue, thus playing an increasingly important role in disaster management and rescue. This article reviews the technologies and methods required to apply artificial intelligence to rescue robot teams. Firstly, the feasibility of motion control for swarm robots was explored from the perspective of biomimetic robots. Through the analysis of animal biomimetics and the comparison of commonly used topological structures, the nature of team rescue robot rescue is emphasized, and based on this, a scheme for optimizing topological networks by combining environmental intelligence is proposed. Secondly, several existing micro robots were introduced and their data loading capabilities were evaluated. On this basis, the process of robot vision and motion commands was outlined. At the meanwhile, researchers focus on the current mainstream robot motion trajectory algorithms, and study the algorithm optimization process from extending the motion path planning of a single robot to group coordinated motion. This includes traditional cell decomposition algorithms and algorithms combined with machine learning to improve path planning efficiency. Finally, the above methods were summarized, and the impact of other possible feasible methods in the field of artificial intelligence was explored and analyzed.