Multi-robot Cooperative Pursuit Based on Association Rule Data Mining

Abstract

An approach of cooperative hunting for multiple mobile targets by multi-robot is presented, which divides the pursuiting process into forming the pursuiting groups and capturing the targets. The data sets of attribute relationship is built by consulting many factors about capturing evaders, then the interesting rules can be found by data mining from the data sets to build the pursuiting groups. Through doping out the positions of targets, the members of pursuiting can confirm their destinations. Based on these extensions, a kind of multi-robot cooperative pursuit algorithm that allows dynamic alliance is proposed. 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 dynamic environment .

A novel approach for multi-agent cooperative pursuit to capture grouped evaders

“…Reorganization is also referred as flexibility. There has been many useful and novel approaches applied to improve cooperative multi-agent systems (MAS), in which some researchers focus on interaction between the agents and the environment such as graph theory [3], polygonal environment [4], cellular environment [5] and some others researchers focus on mechanisms of cooperation among human individuals and tries to find out different ways to apply multi agent pursuit effectively. For instance, Awang Chen et al proposed a new hunting strategy based on optimized quick surrounding and quick-capture direction [6].…”

“…In which from step 2 to step 12, Q(s,a) is continuously changing until all Q(s,a) becomes optimal. 5…”

“…Cooperation was considered an important aspect in a quicker pursuit in [5] where authors proposed a strategy based on pursuit cooperation using association rule of data mining technology. It was discussed in many other problems like task allocation for multi-agents to make them cooperate on related tasks just as in [22].…”

Multi-AUV Hunting Algorithm Based on Bio-inspired Neural Network in Unknown Environments

“…For easy discussion, it is assumed that there are four hunting AUVs with only one target. The initial location of the target is (11,6). The hunting AUVs are P C 1 , P C 2 , P C 3 , P C 4 and the initial positions of them Figure 6(b) shows the hunting process for the first seven steps.…”

“…However, many complicated tasks nowadays go beyond the single AUV's capability. Multi-AUV systems, in recent years, have been studied in areas such as formation [3][4], localization [5], cooperative hunting [6][7][8], cooperation searching [9], path planning [10][11], task assignment and cooperation [12][13][14][15], due to their outstanding robustness and high efficiency of coordination and collaboration. Among the areas mentioned above, the multi-AUV hunting problem has attracted much attention, because it can be applied in military tasks and is a good verification of cooperation and coordination of a multi-AUV system.…”