Sweet pepper pose detection and grasping for automated crop harvesting

Lehnert, Christopher, Sa, Inkyu, McCool, Christopher, Upcroft, Ben, & Perez, Tristan (2016) Sweet pepper pose detection and grasping for automated crop harvesting. In IEEE International Conference on Robotics and Automation (ICRA 2016), 16-21 September 2016, Stockholm, Sweden.

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Abstract

This paper presents a method for estimating the 6DOF pose of sweet-pepper (capsicum) crops for autonomous harvesting via a robotic manipulator. The method uses the Kinect Fusion algorithm to robustly fuse RGB-D data from an eye-in-hand camera combined with a colour segmentation and clustering step to extract an accurate representation of the crop. The 6DOF pose of the sweet peppers is then estimated via a nonlinear least squares optimisation by fitting a superellipsoid to the segmented sweet pepper. The performance of the method is demonstrated on a real 6DOF manipulator with a custom gripper. The method is shown to estimate the 6DOF pose successfully enabling the manipulator to grasp sweet peppers for a range of different orientations. The results obtained improve largely on the performance of grasping when compared to a naive approach, which does not estimate the orientation of the crop.

Impact and interest:

1 citations in Scopus
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ID Code: 95756
Item Type: Conference Paper
Refereed: Yes
Additional URLs:
Keywords: Robot manipulation, Manipulation Planning, Object localisation, Agricultural Automation
Subjects: Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Computer Vision (080104)
Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Image Processing (080106)
Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > ELECTRICAL AND ELECTRONIC ENGINEERING (090600) > Control Systems Robotics and Automation (090602)
Divisions: Current > Research Centres > ARC Centre of Excellence for Robotic Vision
Current > Schools > School of Electrical Engineering & Computer Science
Current > Institutes > Institute for Future Environments
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Funding:
Copyright Owner: Copyright 2016 [Please consult the author]
Deposited On: 25 May 2016 22:35
Last Modified: 12 Dec 2016 15:57

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