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Dynamic task allocation method based on immune system for cooperative robots

Yunyuan Gao, Zhizeng Luo

Year
2008
Citations
7

Abstract

To accomplish unknown cooperative tasks in multi-robot system, an efficient task allocation method and autonomous cooperation among robots are required. This paper fully takes advantage of the interactions among antibodies and antigen stimulus of immune system to solve the problem. Firstly, an Artificial Immune Network (AIN) model for multi-robot system is presented with autonomously distributed architecture. Based on AIN, the immune-based static task allocation algorithm is designed utilizing the interactions among the antibodies from inter- and intra-robot. Then the dynamic task allocation method is developed and extended by integrating the cooperative idea into the antigen stimulus. By the self-reinforcement learning of the antigen stimulus, the autonomous cooperation among robots is realized and deadlock situation is avoided. The dynamic allocation method for cooperative robots is demonstrated and analyzed in the simulation of emergency handling, in which a group of robots must detect alarms and cooperatively fix problems indicated by those alarms.

Keywords

RobotComputer scienceArtificial immune systemDistributed computingTask (project management)DeadlockReinforcement learningArtificial intelligenceEngineering

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