Laser & Optoelectronics Progress, Volume. 62, Issue 10, 1015009(2025)
Multiscale Regional-Attention Stacked-Object Grasp Detection Network
[1] Mao L B, Shi J L, Zhou Z Q et al. Robot grasping method based on single view key point voting[J]. Computer Integrated Manufacturing Systems, 29, 3572-3581(2023).
[3] Morales A, Sanz P J, del Pobil A P. Vision-based computation of three-finger grasps on unknown planar objects[C], 1711-1716(2002).
[13] Zhong X G, Xu M, Zhong X Y et al. Multimodal features deep learning for robotic potential grasp recognition[J]. Acta Automatica Sinica, 42, 1022-1029(2016).
[17] Xu Z C, Xue J P, Sun P F et al. Robot grasp detection method based on stable lightweight network[J]. Chinese Journal of Lasers, 50, 1304003(2023).
[18] An G L, Li Z G, Du Y J et al. Multiple workpiece grasping point localization method based on deep learning[J]. Laser & Optoelectronics Progress, 60, 1215002(2023).
[19] Meng Y B, Huang Q, Han J Q et al. Robot dynamic object positioning and grasping method based on two stages[J]. Laser & Optoelectronics Progress, 60, 0615005(2023).
Get Citation
Copy Citation Text
Shengjun Xu, Zhiwei Cui, Ya Shi, Xiaohan Li, Erhu Liu, Abdelhamid Hameg. Multiscale Regional-Attention Stacked-Object Grasp Detection Network[J]. Laser & Optoelectronics Progress, 2025, 62(10): 1015009
Category: Machine Vision
Received: Aug. 19, 2024
Accepted: Nov. 26, 2024
Published Online: Apr. 22, 2025
The Author Email: Zhiwei Cui (18092538006@163.com)
CSTR:32186.14.LOP241866