Multi-robot Cooperative Space Exploration Method Based on Rapidly-exploring Random Trees and Greedy Frontier-based Exploration

Aiming at the problems of poor robustness, low exploration efficiency and incomplete perception of environmental obstacles in traditional multi-robot cooperative exploration algorithm, a novel multi-robot cooperative space exploration method is proposed based on rapidly-exploring random tree and greedy frontier-based exploration (RRT-GFE). Firstly, Thiessen polygons are used to model and partition the environments, and RRT frontier exploration algorithm is used to explore all Thiessen polygons in turn. Secondly, GFE algorithm is introduced to refine the search results based on the RRT frontier exploration algorithm, and the centroid of continuous frontier region is extracted as the exploration target point. Then, a multi-robot task assignment method based on the improved market mechanism is introduced to dynamically assign the exploration target points based on the divided polygon regions and the extracted frontier points, and the map-merging algorithm is used in the exploration process to merge several local maps in real time. Finally, a simulation/prototype experiment platform is built based on the Robot Operating System (ROS) and a series of experiments are carried out. The results show that the multi-robot cooperative exploration algorithm based on RRT-GFE can reduce the time cost and improve the exploration efficiency in both the simulations and the prototype experiments.