Intelligent navigation and accurate positioning of an assist robot in indoor environments

Bin Hua; Endri Rama; Genci Capi; Mitsuru Jindai; Yosuke Tsuri

doi:10.1117/12.2304676

19 December 2017 Intelligent navigation and accurate positioning of an assist robot in indoor environments

Bin Hua, Endri Rama, Genci Capi, Mitsuru Jindai, Yosuke Tsuri

Proceedings Volume 10613, 2017 International Conference on Robotics and Machine Vision; 106130O (2017) https://doi.org/10.1117/12.2304676
Event: Second International Conference on Robotics and Machine Vision, 2017, Kitakyushu, Japan

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.

Citation Download Citation

Bin Hua, Endri Rama, Genci Capi, Mitsuru Jindai, and Yosuke Tsuri "Intelligent navigation and accurate positioning of an assist robot in indoor environments", Proc. SPIE 10613, 2017 International Conference on Robotics and Machine Vision, 106130O (19 December 2017); https://doi.org/10.1117/12.2304676

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