Recent Developments in Robotic Grasping Detection
Author:
Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-54288-6_4
Reference16 articles.
1. Du, G., Wang, K., Lian, S., Zhao, K.: Vision-based robotic grasping from object localization, object pose estimation to grasp estimation for parallel grippers: a review. Artif. Intell. Rev. 54, 1677–1734 (2021)
2. Tian, H., et al.: Data-driven robotic visual grasping detection for unknown objects: a problem-oriented review. Expert Syst. Appl. 211, 118624 (2023)
3. Zhou, Z., et al.: Learning-based object detection and localization for a mobile robot manipulator in SME production. Robot. Comput. Integr. Manuf. 73, 102229 (2022)
4. Qi, C.R., Chen, X., Litany, O., Guibas, L.J.: ImVoteNet: boosting 3D object detection in point clouds with image votes. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp. 4404–4413 (2020)
5. Da Rold, A., Furiato, M., Zaki, A.M.A., Carnevale, M., Giberti, H.: Deep learning-based robotic sorter for flexible production. Procedia Comput. Sci. 217, 1579–1588 (2023)
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