Predicting the robot's grip capacity on different objects using multi-object grasping
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Springer Science and Business Media LLC
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https://link.springer.com/content/pdf/10.1007/s41315-024-00342-1.pdf
Reference22 articles.
1. J.-C. Pang et al., Object-Oriented Option Framework for Robotics Manipulation in Clutter. pp. 1230–1237, 2023, https://doi.org/10.1109/IROS55552.2023.10342335.
2. Wu, G., Chen, W., Cheng, H., Zuo, W., Zhang, D., You, J.: Multi-object grasping detection with hierarchical feature fusion. IEEE Access 7, 43884–43894 (2019). https://doi.org/10.1109/ACCESS.2019.2908281
3. T. Chen, A. Shenoy, A. Kolinko, S. Shah, and Y. Sun, “Multi-Object Grasping – Estimating the Number of Objects in a Robotic Grasp,” in 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), IEEE, 2021, pp. 4995–5001. https://doi.org/10.1109/IROS51168.2021.9636777.
4. S. Joshi, S. Kumra, and F. Sahin, “Robotic Grasping using Deep Reinforcement Learning. In: 2020 IEEE 16th International Conference on Automation Science and Engineering (CASE), IEEE, 2020, pp. 1461–1466. https://doi.org/10.1109/CASE48305.2020.9216986.
5. H. Karaoguz and P. Jensfelt, Object Detection Approach for Robot Grasp Detection. In: 2019 International Conference on Robotics and Automation (ICRA), IEEE, May 2019, pp. 4953–4959. https://doi.org/10.1109/ICRA.2019.8793751.
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