A Grasping System with Structured Light 3D Machine Vision Guided Strategy Optimization
Author:
Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-40286-9_31
Reference25 articles.
1. Du, S.: Vision-based robotic grasping from object localization, object pose estimation to grasp estimation for parallel grippers: a review. Artif. Intell. Rev. Int. Sci. Eng. J. 54(3) (2021)
2. Rusu, R.B., Bradski, G.R., Thibaux, R., et al.: Fast 3D recognition and pose using the viewpoint feature histogram. In: 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems, 18–22 October 2010, Taipei, Taiwan. IEEE (2010)
3. Drost, B., Ulrich, M., Navab, N., et al.: Model globally, match locally: efficient and robust 3D object recognition. IEEE (2010)
4. Wang, H., Wang, H., Zhuang, C.: 6D pose estimation from point cloud using an improved point pair features method. In: International Conference on Control, Automation and Robotics. IEEE (2021)
5. Yang, Y., Liu, Y., Liang, H., et al.: Attribute-based robotic grasping with one-grasp adaptation (2021)
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