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JRM Vol.28 No.2 pp. 149-157
doi: 10.20965/jrm.2016.p0149
(2016)

Paper:

Support System for Slope Shaping Based on a Teleoperated Construction Robot

Katsutoshi Ootsubo*, Daichi Kato**, Takuya Kawamura*, and Hironao Yamada*

*Gifu University
1-1 Yanagido, Gifu City, Gifu 501-1193, Japan

**Amada Machine Tools Co., Ltd.
200 Ishida, Isehara City, Kanagawa 259-1196, Japan

Received:
October 17, 2015
Accepted:
February 8, 2016
Published:
April 20, 2016
Keywords:
construction robot, teleoperation, slope shaping, augmented reality
Abstract
Slope shaping is important for the prevention of and recovery from sediment disasters. Because of the danger of direct operation at disaster scenes, teleoperation is the most efficient method for slope shaping. In this paper, we propose a support system for the teleoperation of slope shaping using a construction robot. The system is composed of two sub-systems: an Augmented Reality (AR) finishing stake system and a system for evaluating finished shape deviation. The former is an AR system which presents a virtual finishing stake to the operator of a construction robot. The latter is an evaluation system which measures the actual shape of the slope in 3D and presents its deviation from the planned shape. Moreover, we developed multiple Computer Graphics (CG) patterns of the virtual finishing stake. In this study, first, we verified the usefulness of a real finishing stake quantitatively via subjective experiments. Then we verified the effectiveness of our proposed systems and identified the optimal CG pattern of the virtual finishing stake via the experiments. Based on the results, we discuss the usefulness of the finishing stake and the effectiveness of our system for slope shaping using a teleoperated construction robot.
Slope shaping by using our proposed system

Slope shaping by using our proposed system

Cite this article as:
K. Ootsubo, D. Kato, T. Kawamura, and H. Yamada, “Support System for Slope Shaping Based on a Teleoperated Construction Robot,” J. Robot. Mechatron., Vol.28 No.2, pp. 149-157, 2016.
Data files:
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Last updated on Dec. 02, 2024