Vision Based Autonomous Orientational Control for Aerial Manipulation via On-Board FPGA

Leewiwatwong Suphachart, Shouhei Shimahara, Robert Ladig, Kazuhiro Shimonomura; Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2016, pp. 36-42

Abstract


We describe an FPGA-based on-board control system for autonomous orientation of an aerial robot to assist aerial manipulation tasks. The system is able to apply yaw control to aid an operator to precisely position a drone when it is nearby a bar-like object. This is achieved by applying parallel Hough transform enhanced with a novel image space separation method, enabling highly reliable results in various circumstances combined with high performance. The feasibility of this approach is shown by applying the system to a multi-rotor aerial robot equipped with an upward directed robotic hand on top of the airframe developed for high altitude manipulation tasks. In order to grasp a bar-like object, orientation of the bar object is observed from the image data obtained by a monocular camera mounted on the robot. This data is then analyzed by the on-board FPGA system to control yaw angle of the aerial robot. In experiments, reliable yaw-orientation control of the aerial robot is achieved.

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[bibtex]
@InProceedings{Suphachart_2016_CVPR_Workshops,
author = {Suphachart, Leewiwatwong and Shimahara, Shouhei and Ladig, Robert and Shimonomura, Kazuhiro},
title = {Vision Based Autonomous Orientational Control for Aerial Manipulation via On-Board FPGA},
booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},
month = {June},
year = {2016}
}