Task Allocation Based on the Immune Network Adjusted by the Leukocyte in the Multi-Robot Systems

摘要

In order to solve the task allocation in the autonomous cooperation of the multi-robot systems, a novel artificial immune network allocation model adjusted by the leukocyte is presented in this study. Inspired by the Jerne?s idiotypic immune network hypothesis, the stimulation between the antibody and antigen and the stimulation and suppression among different antibodies are defined firstly through regarding the B-cell, antibody and task as the robot, robot behavior and antigen, respectively. In order to further improve the allocation efficiency of the multi-robot systems, a novel immune network allocation model with the leukocyte adjustment is presented according to the biological mechanisms of the leukocyte. Moreover, the immune memory is introduced to improve the allocation efficiency and the dynamic adaptability of the artificial immune system. Compared with other immune algorithm, the simulation results in several environments show that the proposed allocation algorithm obviously improves the cooperation performance and reduces the consumption time, transport distance and energy waste of the task, which verifies the effectiveness of the proposed algorithm.