Computational Intelligence for Mobile Robotic Systems – Decision Making, Learning, and Planning –

Toshio Fukuda; Naoyuki Kubota

doi:10.20965/jrm.2000.p0194

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JRM Vol.12 No.3 pp. 194-201

doi: 10.20965/jrm.2000.p0194

(2000)

Paper:

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Computational Intelligence for Mobile Robotic Systems – Decision Making, Learning, and Planning –

Toshio Fukuda^* and Naoyuki Kubota^**

^*Center for Cooperative Research in Advanced Science and Technology, Dept. of Mechano-Informatics and Systems, Dept. of Micro System Engineering, Nagoya University, Furo-cho, Chikusa-ku, Nagoya, 464-8603, Japan

^**Department of Human and Artificial Intelligent Systems, Fukui University, 3-9-1 Bunkyo, Fukui 910-8507, Japan

Received:

February 14, 2000

Accepted:

March 15, 2000

Published:

June 20, 2000

Keywords:

computational intelligence, robotics, coevolutionary computation, planning, decision making

Abstract

This paper describes recent topics of computational intelligence. The intelligent capabilities will be required for the various systems to adapt to dynamically changing environments. First, we introduce the computational intelligence including evolutionary computing, neural computing, and fuzzy computing. Next, some of the important problems including the system architecture, structured intelligence, emerging system, and implementation methods are discussed for mobile robotic systems from the viewpoint of coevolution.

Cite this article as:

T. Fukuda and N. Kubota, “Computational Intelligence for Mobile Robotic Systems – Decision Making, Learning, and Planning –,” J. Robot. Mechatron., Vol.12, No.3, pp. 194-201, 2000.

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

Computational Intelligence for Mobile Robotic Systems – Decision Making, Learning, and Planning –

Toshio Fukuda* and Naoyuki Kubota**

Toshio Fukuda^* and Naoyuki Kubota^**