基于神经网络的自主移动机器人实时学习

Proceedings Sixth Euromicro Workshop on Real-Time Systems Pub Date : 1994-06-15 DOI:10.1109/EMWRTS.1994.336867

U. Zimmer, E. Puttkamer

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引用次数: 15

摘要

我们讨论了神经网络聚类技术在移动机器人上的应用，以建立定性的拓扑环境图。这必须实时完成，也就是说，内部世界模型必须适应传感器样本流，而不可能停止数据流。我们的实验是在模拟环境和机器人ALICE上完成的。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Realtime-learning on an autonomous mobile robot with neural networks

We discuss the usage of neural network clustering techniques on a mobile robot, in order to build qualitative topologic environment maps. This has to be done in realtime, i.e. the internal world-model has to be adapted by the flow of sensor-samples without the possibility to stop this data flow. Our experiments are done in a simulation environment as well as on a robot, called ALICE.<>

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Proceedings Sixth Euromicro Workshop on Real-Time Systems

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