Sweet pepper pose detection and grasping for automated crop harvesting

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 t...

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Bibliographic Details
Published in2016 IEEE International Conference on Robotics and Automation (ICRA) pp. 2428 - 2434
Main Authors Lehnert, Christopher, Inkyu Sa, McCool, Christopher, Upcroft, Ben, Perez, Tristan
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.05.2016
Subjects
Agriculture
Cameras
Image color analysis
Manipulators
Robot vision systems
Three-dimensional displays
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Summary: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.
DOI:10.1109/ICRA.2016.7487394