The Brain-Like Sensorimotor Control System

  • Authors:
  • Takamasa Koshizen; Yugo Ueda; Hiroshi Tsujino

  • Affiliations:
  • Wako Research Centre, Honda RD Co. Ltd., 1-4-1 Chuo Wako-Shi, Saitama 351-0193, Japan/ e-mail:;Wako Research Centre, Honda RD Co. Ltd., 1-4-1 Chuo Wako-Shi, Saitama 351-0193, Japan/ e-mail:;Wako Research Centre, Honda RD Co. Ltd., 1-4-1 Chuo Wako-Shi, Saitama 351-0193, Japan/ e-mail:

  • Venue:
  • Journal of Intelligent and Robotic Systems
  • Year:
  • 2002

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Abstract

In this paper, we propose brain-like (BL) sensorimotor control system that is assumed to be composed of its unconscious and conscious part. The conscious part of BL sensorimotor control system is emerged when Prefrontal Cortex (PFC) acts with respect to spatiotemporal selective attention mechanism in particular. In our framework, the selective attention can be induced by Baye's rule comprising of PFC-based neural network where both unsupervised and supervised learning schemes are employed. A preliminary experiment is manually carried out to analyse human control mechanism for the stability of RC-helicopter. As a result, we suggest the relationship between the selective attention and the minimum variance theory. BL sensorimotor control system is favorably considered to build subject to suffice the minimum variance theory that is the key for computing spatiotemporal selective attention mechanism, computed by the PFC-based neural network. In this paper, the network is also examined with respect to control the RC-helicopter and the result shows the soundness of BL sensorimotor control system.