Towards Hierarchical Self-Optimization in Autonomous Groups of Mobile Robots

摘要：

We present a real-world scenario for investigating and demonstrating hierarchical self-optimization in autonomous groups of mobile robots. The scenario is highly dynamic and easily expandable. It offers adequate starting points for the integration of hierarchical self-optimization. Reinforcement learning, e. g., can be introduced in order to improve the individual behavior of a single robot. Also swarm intelligence algorithms can improve the overall team behavior with respect to common goals. A reference behavior system incorporating a dynamic role assignment and hierarchical state machines was implemented and has been applied to the miniature robot BeBot. The system was evaluated by conducting several tests.

作者: Thomas Schierbaum Alexander Jungmann Christoph Rasche

作者单位: Product Engineering, Heinz Nixdorf InstituteUniversity of Paderborn, Germany Benjamin Werdehausen and Bernd KleinjohannC-LABUniversity of Paderborn, Germany Benjamin Werdehausen and Bernd Kleinjohann C-LAB University of Paderborn, Germany

会议类型: 国际会议

会议名称: IEEE 10th International Conference on Industrial Informatics(第十届IEEE工业信息学国际学术会议 INDIN2012)

会议地点: 北京

会议语种:英文

页码: 1098-1103

在线出版日期: 2012-07-25（万方平台首次上网日期，不代表论文的发表时间）