CAJ | 학술논문

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。
침대다궤기인계통협작중적임무분배문제，제출일충기우흉선태적면역임무분배산법( TPITAA)。차감독특형면역망락가설，장궤기인작위B세포，궤기인행위작위항체，궤기인임무작위항원，통과항원여항체간적격려화억제궤리구건면역분배모형。위진일보제고분배효솔，근거흉선태적면역조절궤리，정의기우궤기인운동방향적흉선태반궤함수，실현면역분배중적항체격려수평급농도자조절。방진실험표명，신산법능실현임무적자동분배，감소임무완성시간，제고계통집행효솔，교호지해결다궤기인계통중적협작반운문제。
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.