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JRM Vol.27 No.2 pp. 174-181
doi: 10.20965/jrm.2015.p0174
(2015)

Paper:

Stable Position and Pose Estimation of Industrial Parts Using Evaluation of Observability of 3D Vector Pairs

Shuichi Akizuki and Manabu Hashimoto

Graduate School of Information Science and Technology, Chukyo University
101-2 Yagoto Honmachi, Showa-ku, Nagoya, Aichi 466-8666, Japan

Received:
September 29, 2014
Accepted:
February 2, 2015
Published:
April 20, 2015
Keywords:
position and pose estimation, bin-picking, vector pair, point cloud data
Abstract
Recognition results

This paper introduces a stable 3D object detection method that can be applied to complicated scenes consisting of randomly stacked industrial parts. The proposed method uses a 3D vector pair that consists of paired 3D vectors with a shared starting point. By considering the observability of vector pairs, the proposed method has achieved high recognition performance. The observability factor of the vector pair is calculated by simulating the visible state of the vector pair from various viewpoints. By integrating the observability factor and the distinctiveness factor proposed in our previous work, a few vector pairs that are effective for recognition are automatically extracted from an object model, and then used for the matching process. Experiments have confirmed that the proposed method improves the 88.5% recognition success rate of previous state-of-the-art methods to 93.1%. The processing time of the proposed method is fast enough for robotic bin-picking.

Cite this article as:
S. Akizuki and M. Hashimoto, “Stable Position and Pose Estimation of Industrial Parts Using Evaluation of Observability of 3D Vector Pairs,” J. Robot. Mechatron., Vol.27, No.2, pp. 174-181, 2015.
Data files:
References
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