Evolutionary trajectory learning for autonomous robots by means of geometric approximations of polygonal obstacles

M. M A Hashem, Keigo Watanabe, Kiyotaka Izumi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper addresses the issue of flexible geometric approximations of polygonal obstacles for Intelligent Autonomous Robot (IAR) navigation which is the extension of our previous work. The trajectory learning problem for IAR navigation is formulated as a constrained discrete-time-optimal control problem where the polygonal obstacles are the constraints. From the visibility and sensor modeling concepts, polygonal obstacles within the environment are approximated as either by circles or by ellipses depending on the shape and size of them. Furthermore, some practical issues are identified and resolved through these type of approximations. The effectiveness of these methods is illustrated by some simulations of the robot within a heavily obstacle environment.

Original languageEnglish
Title of host publicationProceedings of the IEEE International Conference on Systems, Man and Cybernetics
PublisherIEEE
Volume2
Publication statusPublished - 1999
Externally publishedYes
Event1999 IEEE International Conference on Systems, Man, and Cybernetics 'Human Communication and Cybernetics' - Tokyo, Jpn
Duration: Oct 12 1999Oct 15 1999

Other

Other1999 IEEE International Conference on Systems, Man, and Cybernetics 'Human Communication and Cybernetics'
CityTokyo, Jpn
Period10/12/9910/15/99

Fingerprint

Trajectories
Robots
Navigation
Visibility
Sensors

ASJC Scopus subject areas

  • Hardware and Architecture
  • Control and Systems Engineering

Cite this

Hashem, M. M. A., Watanabe, K., & Izumi, K. (1999). Evolutionary trajectory learning for autonomous robots by means of geometric approximations of polygonal obstacles. In Proceedings of the IEEE International Conference on Systems, Man and Cybernetics (Vol. 2). IEEE.

Evolutionary trajectory learning for autonomous robots by means of geometric approximations of polygonal obstacles. / Hashem, M. M A; Watanabe, Keigo; Izumi, Kiyotaka.

Proceedings of the IEEE International Conference on Systems, Man and Cybernetics. Vol. 2 IEEE, 1999.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Hashem, MMA, Watanabe, K & Izumi, K 1999, Evolutionary trajectory learning for autonomous robots by means of geometric approximations of polygonal obstacles. in Proceedings of the IEEE International Conference on Systems, Man and Cybernetics. vol. 2, IEEE, 1999 IEEE International Conference on Systems, Man, and Cybernetics 'Human Communication and Cybernetics', Tokyo, Jpn, 10/12/99.
Hashem MMA, Watanabe K, Izumi K. Evolutionary trajectory learning for autonomous robots by means of geometric approximations of polygonal obstacles. In Proceedings of the IEEE International Conference on Systems, Man and Cybernetics. Vol. 2. IEEE. 1999
Hashem, M. M A ; Watanabe, Keigo ; Izumi, Kiyotaka. / Evolutionary trajectory learning for autonomous robots by means of geometric approximations of polygonal obstacles. Proceedings of the IEEE International Conference on Systems, Man and Cybernetics. Vol. 2 IEEE, 1999.
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