Abstract
In this paper, we investigate the problem of grasping novel objects in unstructured environments. Object geometry, reachability, and force closure analysis are considered to address this problem. A framework is proposed for grasping unknown objects by localizing contact regions on the contours formed by a set of depth edges generated from a single view 2D depth image. Specifically, contact regions are determined based on edge geometric features derived from analysis of the depth map data. Finally, the performance of the approach is successfully validated by applying it to the scenes with both single and multiple objects, in both MATLAB simulation and experiments using a Kinect One sensor and a Baxter manipulator.
This study was funded in part by NIDILRR grant #H133G120275, and in part by NSF grant numbers IIS-1409823 and IIS-1527794. However, these contents do not necessarily represent the policy of the aforementioned funding agencies, and you should not assume endorsement by the Federal Government.
A. Jabalameli and N. Ettehadi are graduate students with the Electrical and Computer Engineering Dept. at the University of Central Florida (UCF), Orlando, FL 32816.
A. Behal is with ECE and NanoScience Technology Center at UCF, Orlando, FL.
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Jabalameli, A., Ettehadi, N., Behal, A. (2020). Near Real-Time Robotic Grasping of Novel Objects in Cluttered Scenes. In: Arai, K., Kapoor, S. (eds) Advances in Computer Vision. CVC 2019. Advances in Intelligent Systems and Computing, vol 944. Springer, Cham. https://doi.org/10.1007/978-3-030-17798-0_28
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