A target-reaching controller for mobile robots using spiking neural networks
ICONIP'12 Proceedings of the 19th international conference on Neural Information Processing - Volume Part IV
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Autonomous mobile robot is a hot research topic and attracts many interests due to that mobile robot has been or will be employed in various fields, such as space exploration, under water survey, industrial and military industries, service and medical applications, and so on. Wall-following strategy can help the mobile robot to avoid deadlock caused by local minim and fulfill the given task effectively. Spiking Neural Networks (SNNs), the third generation of the neural networks, is suitable in the design of mobile robot behavior's controller. In this paper, a wall-following controller based on SNNs for mobile robot is presented. Pulse frequency codes and pulse temporal coincidence detection codes are used in the proposed SNN controller. The designed controller can not only control the robot to follow the wall successfully, but also can be easily implemented.