Immune Task Allocation for Multi-robot System Based on Adjustment Mechanism of Thymic Peptide
YUAN Ming-Xin1,LI Ping-Zheng1,JIANG Ya-Feng1, WANG Sun-An2
1.School of Mechatronics-Engineering and Automotive, Jiangsu University of Science and Technology, Zhangjiagang 215600
2.School of Mechanical Engineering, Xi′an Jiaotong University, Xi′an 710049
To solve the task allocation in multi-robot system, a thymic peptide based immune task allocation algorithm (TPITAA) is proposed. Inspired by the mechanism of idiotypic network hypothesis, an immune allocation model is constructed according to the stimulation and suppression among the antigen and antibodies. The robot, robot behavior and task are taken as B cell, antibody and antigen respectively. To further improve the allocation efficiency, a thymic peptide feedback function based on movement direction of robot is defined according to the immune adjustment mechanism of thymic peptide, which realizes the self-adjustment of antibody stimulation level and antibody concentration. The simulation results show that the proposed algorithm realizes the automatic allocation for tasks, reduces the completion time, improves the operating efficiency and solves the cooperation handling well in multi-robot system.
袁明新,李平正,江亚峰,王孙安. null[J]. 模式识别与人工智能, 2014, 27(5): 472-480.
YUAN Ming-Xin,LI Ping-Zheng,JIANG Ya-Feng, WANG Sun-An. Immune Task Allocation for Multi-robot System Based on Adjustment Mechanism of Thymic Peptide. , 2014, 27(5): 472-480.
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