Hough-space-based object recognition tightly coupled with path planning for robust and fast bin-picking

Ayako Takenouchi, Naoyoshi Kanamaru, Makoto Mizukawa

Research output: Chapter in Book/Report/Conference proceedingConference contribution

8 Citations (Scopus)

Abstract

The proposed bin-picking method combines object recognition with path planning. To avoid conflicts between the assumptions of the elemental techniques needed for bin-picking, object recognition is combined with path planning by using environmental information. To achieve this combination, a Hough transform, which records the model-to-image matches in a Hough space, is used to estimate the pose. The matches represent the arrangement of the objects, so they can be regarded as environmental information for path planning. To reduce the number of recognition errors and the object-detection time, a pair of object features that reduces the number of invalid votes in the Hough space is used for the Hough transform. Simulated path planning showed that using a Hough space to represent the environmental information improves the ability to plan a safe path for the manipulator. Simulated object recognition showed that using a pair of features makes the process faster and reduces the number of invalid votes. The pose estimation and safe path planning ability were confirmed by an experiment on casting objects using a range finder and a robot.

Original languageEnglish
Title of host publicationIEEE International Conference on Intelligent Robots and Systems
Editors Anon
Place of PublicationPiscataway, NJ, United States
PublisherIEEE
Pages1222-1229
Number of pages8
Volume2
Publication statusPublished - 1998
EventProceedings of the 1998 IEEE/RSJ International Conference on Intelligent Robots and Systems. Part 1 (of 3) - Victoria, Can
Duration: 1998 Oct 131998 Oct 17

Other

OtherProceedings of the 1998 IEEE/RSJ International Conference on Intelligent Robots and Systems. Part 1 (of 3)
CityVictoria, Can
Period98/10/1398/10/17

Fingerprint

Object recognition
Bins
Motion planning
Hough transforms
Range finders
Manipulators
Casting
Robots
Experiments

ASJC Scopus subject areas

  • Control and Systems Engineering

Cite this

Takenouchi, A., Kanamaru, N., & Mizukawa, M. (1998). Hough-space-based object recognition tightly coupled with path planning for robust and fast bin-picking. In Anon (Ed.), IEEE International Conference on Intelligent Robots and Systems (Vol. 2, pp. 1222-1229). Piscataway, NJ, United States: IEEE.

Hough-space-based object recognition tightly coupled with path planning for robust and fast bin-picking. / Takenouchi, Ayako; Kanamaru, Naoyoshi; Mizukawa, Makoto.

IEEE International Conference on Intelligent Robots and Systems. ed. / Anon. Vol. 2 Piscataway, NJ, United States : IEEE, 1998. p. 1222-1229.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Takenouchi, A, Kanamaru, N & Mizukawa, M 1998, Hough-space-based object recognition tightly coupled with path planning for robust and fast bin-picking. in Anon (ed.), IEEE International Conference on Intelligent Robots and Systems. vol. 2, IEEE, Piscataway, NJ, United States, pp. 1222-1229, Proceedings of the 1998 IEEE/RSJ International Conference on Intelligent Robots and Systems. Part 1 (of 3), Victoria, Can, 98/10/13.
Takenouchi A, Kanamaru N, Mizukawa M. Hough-space-based object recognition tightly coupled with path planning for robust and fast bin-picking. In Anon, editor, IEEE International Conference on Intelligent Robots and Systems. Vol. 2. Piscataway, NJ, United States: IEEE. 1998. p. 1222-1229
Takenouchi, Ayako ; Kanamaru, Naoyoshi ; Mizukawa, Makoto. / Hough-space-based object recognition tightly coupled with path planning for robust and fast bin-picking. IEEE International Conference on Intelligent Robots and Systems. editor / Anon. Vol. 2 Piscataway, NJ, United States : IEEE, 1998. pp. 1222-1229
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