Task allocation based on the immune network adjusted by the leukocyte in the multi-robot systems

Abstract

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 J erne's idiotypic immune network hypothesis, the stimulation between the antibody and antigen and die 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 otter immune algorithm, the simulation results in several environments show tliat the proposed allocation algorithm obviously improves the cooperation performance and reduces the consumption time, transport distance and energy waste of tire task, which verifies the effectiveness of the proposed algorithm.