Abstract
An approach of cooperative hunting for multiple mobile targets by multi-robot is presented, which divides the pursuit process into forming the pursuit teams and capturing the targets. The data sets of attribute relationship is built by consulting all of factors about capturing evaders, then the interesting rules can be found by data mining from the data sets to build the pursuit teams. Through doping out the positions of targets, the pursuit game can be transformed into multi-robot path planning. Reinforcement learning is used to find the best path. The simulation results show that the mobile evaders can be captured effectively and efficiently, and prove the feasibility and validity of the given algorithm under a dynamic environment.
Highlights
In multiagent systems it is quite an important and interesting endeavor to study the development of cooperative behavior among agents
In this paper we propose an approach of cooperative hunting for multiple mobile targets by multi-robot
There are two parts: one in which the sample data set by the attribute relationship between predators and evaders is created, association rule data mining technology is used to find out the interesting rules, to build the pursuit team to every evader according to these rules; the other in which every pursuit team forecasts the position of its object in order to make sure of the predators’ aim positions, we can transform the pursuit problem into the path planning problem and use multi-robot reinforcement learning to choose the pursuit teams optimal actions strategies to capture evaders in the shortest time
Summary
In multiagent systems it is quite an important and interesting endeavor to study the development of cooperative behavior among agents. Based on dynamic role assignment, a method for forming coordination multi-robot teams in the multiple mobile targets capturing has been proposed Cai et al (2008) proposed a kind of multi-robot cooperative pursuit algorithm that allows fault injection dynamic alliance based task bundle auction. Based on these researches, in this paper we propose an approach of cooperative hunting for multiple mobile targets by multi-robot. There are two parts: one in which the sample data set by the attribute relationship between predators and evaders is created, association rule data mining technology is used to find out the interesting rules, to build the pursuit team to every evader according to these rules; the other in which every pursuit team forecasts the position of its object in order to make sure of the predators’ aim positions, we can transform the pursuit problem into the path planning problem and use multi-robot reinforcement learning to choose the pursuit teams optimal actions strategies to capture evaders in the shortest time
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