A New Approach of Multi-robot Cooperative Pursuit Based on Association Rule Data Mining

An approach of cooperative hunting for multiple mobile targets by multi-robot is presented, whichdivides the pursuit process into forming the pursuit teams and capturing the targets. The data sets of attributerelationship is built by consulting all of factors about capturing evaders, then the interesting rules can be foundby data mining from the data sets to build the pursuit teams. Through doping out the positions of targets, thepursuit game can be transformed into multi-robot path planning. Reinforcement learning is used to find the bestpath. The simulation results show that the mobile evaders can be captured effectively and efficiently, and prove thefeasibility and validity of the given algorithm under a dynamic environment