基于胸腺肽调节机制的多机器人免疫任务分配  

Immune Task Allocation for Multi-robot System Based on Adjustment Mechanism of Thymic Peptide

作　　者：袁明新[1] 李平正[1] 江亚峰[1] 王孙安[2] 

机构地区：[1]江苏科技大学机电与汽车工程学院,张家港215600 [2]西安交通大学机械工程学院,西安710049

出　　处：《模式识别与人工智能》2014年第5期472-479,共8页Pattern Recognition and Artificial Intelligence

基　　金：国家自然科学基金项目(No.61105071);江苏省高校"青蓝工程"优秀青年骨干教师项目(No.苏教师[2012]39号);江苏科技大学人才引进项目(No.35271004)资助

摘　　要：针对多机器人系统协作中的任务分配问题,提出一种基于胸腺肽的免疫任务分配算法(TPITAA).借鉴独特型免疫网络假设,将机器人作为B细胞,机器人行为作为抗体,机器人任务作为抗原,通过抗原与抗体间的激励和抑制机理构建免疫分配模型.为进一步提高分配效率,根据胸腺肽的免疫调节机理,定义基于机器人运动方向的胸腺肽反馈函数,实现免疫分配中的抗体激励水平及浓度自调节.仿真实验表明,新算法能实现任务的自动分配,减少任务完成时间,提高系统执行效率,较好地解决多机器人系统中的协作搬运问题.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.

关 键 词：任务分配 多机器人系统 免疫网络 胸腺肽 

分 类 号：TP242[自动化与计算机技术—检测技术与自动化装置]