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Task Allocation Algorithm Based On Immune System For Autonomously Cooperative Multi-robot System

机译：自主协作多机器人系统的基于免疫系统的任务分配算法

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摘要

In many cases, tasks are unknown for the multi-robot system in advance. Therefore, robots are required to work cooperatively during the proceeding of tasks. Such cooperation is called autonomous cooperation. To realize autonomous cooperation in the multi-robot system, an appropriate task allocation algorithm is quite important for the efficiency of the system. Taking advantage of the interactions of antibodies and antigen stimulus of the artificial immune system, this paper proposes an immune based task allocation algorithm for the autonomously cooperative robots. Simulating the mechanism of the immune system, the immune-based task allocation algorithm is designed utilizing the interactions among the antibodies from robots. By considering the antibodies from inter- and intra-robot simultaneously, the algorithm is different from other allocation algorithms which are greedy in task allocation. Besides the interactions among the antibodies, the task allocation algorithm is developed by self-reinforcement learning of the antigen stimulus. The autonomous cooperation among robots is realized by adjusting the antigen stimulus. The allocation algorithm for the autonomously cooperative robots is demonstrated and analyzed in the simulation of box fixing, in which a group of robots must work cooperatively to fix boxes with unknown difficulty in advance.
机译：在许多情况下，多机器人系统的任务事先是未知的。因此，要求机器人在执行任务期间协同工作。这种合作称为自主合作。为了在多机器人系统中实现自主协作，适当的任务分配算法对于系统效率非常重要。利用人工免疫系统中抗体与抗原刺激的相互作用，提出了一种基于免疫的自主协作机器人任务分配算法。为了模拟免疫系统的机制，利用来自机器人的抗体之间的相互作用，设计了基于免疫的任务分配算法。通过同时考虑来自内部机器人和内部机器人的抗体，该算法不同于在任务分配中比较贪婪的其他分配算法。除了抗体之间的相互作用外，任务分配算法还通过抗原刺激的自我强化学习来开发。机器人之间的自主协作是通过调节抗原刺激来实现的。在装箱仿真中演示并分析了自主协作机器人的分配算法，在该算法中，一组机器人必须协同工作以预先固定难度未知的箱子。

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