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Proceedings Paper

Intelligent navigation and accurate positioning of an assist robot in indoor environments
Author(s): Bin Hua; Endri Rama; Genci Capi; Mitsuru Jindai; Yosuke Tsuri
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Paper Abstract

Intact robot’s navigation and accurate positioning in indoor environments are still challenging tasks. Especially in robot applications, assisting disabled and/or elderly people in museums/art gallery environments. In this paper, we present a human-like navigation method, where the neural networks control the wheelchair robot to reach the goal location safely, by imitating the supervisor’s motions, and positioning in the intended location. In a museum similar environment, the mobile robot starts navigation from various positions, and uses a low-cost camera to track the target picture, and a laser range finder to make a safe navigation. Results show that the neural controller with the Conjugate Gradient Backpropagation training algorithm gives a robust response to guide the mobile robot accurately to the goal position.

Paper Details

Date Published: 19 December 2017
PDF: 7 pages
Proc. SPIE 10613, 2017 International Conference on Robotics and Machine Vision, 106130O (19 December 2017); doi: 10.1117/12.2304676
Show Author Affiliations
Bin Hua, Univ. of Toyama (Japan)
Endri Rama, Univ. of Toyama (Japan)
Genci Capi, Hosei Univ. (Japan)
Mitsuru Jindai, Univ. of Toyama (Japan)
Yosuke Tsuri, Univ. of Toyama (Japan)

Published in SPIE Proceedings Vol. 10613:
2017 International Conference on Robotics and Machine Vision
Chiharu Ishii; Genci Capi; Jianhong Zhou, Editor(s)

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