High-Performance Active Camera Head Control Using PaLM-Tree

Takayuki Nakamura, Yoshio Sakata, Toshikazu Wada,
and Haiyuan Wu

Department of Computer and Communication Sciences Wakayama University 930 Sakaedani, Wakayama 640-8510, Japan

Received:

May 12, 2009

Accepted:

October 19, 2009

Published:

December 20, 2009

Keywords:

active camera head, feedback error learning, PaLM-tree

Abstract

In this paper, we propose a method for controlling an active camera in tracking a moving target highly accurately using PaLM-tree, an easy-to-use function approximator we developed. Our feedback error learning controller enhanced by PaLM-tree improves accuracy in tracking a moving target. PaLM-tree correctly learns the inverse model in the feedback error learning. Despite unknown mechanical friction and relatively large closed-loop control latency, our active camera head can successfully track eye movement using the feedback error learning controller. Through experimental results, we confirmed that our method achieved better performance control than a tuned feedback controller.

Cite this article as:

T. Nakamura, Y. Sakata, T. Wada, , and H. Wu, “High-Performance Active Camera Head Control Using PaLM-Tree,” J. Robot. Mechatron., Vol.21 No.6, pp. 720-725, 2009.

Data files:

References

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This article is published under a Creative Commons Attribution-NoDerivatives 4.0 Internationa License.

High-Performance Active Camera Head Control Using PaLM-Tree

Takayuki Nakamura, Yoshio Sakata, Toshikazu Wada, and Haiyuan Wu

Takayuki Nakamura, Yoshio Sakata, Toshikazu Wada,
and Haiyuan Wu