Robotic picking in dense clutter via domain invariant learning from synthetic dense cluttered rendering
Robotic picking of diverse range of novel objects is a great challenge in dense clutter, in
which objects are stacked together tightly. However, collecting large-scale dataset with …
which objects are stacked together tightly. However, collecting large-scale dataset with …
Deep learning based 6-DoF antipodal grasp planning from point cloud in random bin-picking task using single-view
Random bin picking is a crucial task in logistic centers, which is driven by E-Commerce
growth. In this letter, we present an end-to-end method for 6-DoF antipodal grasps from …
growth. In this letter, we present an end-to-end method for 6-DoF antipodal grasps from …
Robot suction region prediction method from knowledge to learning in disordered manufacturing scenarios
Suction plays an important role in the disordered manufacturing scenarios because of its
single-point contact and reliability. The prediction of suction region is the primary problem …
single-point contact and reliability. The prediction of suction region is the primary problem …
[HTML][HTML] PolyDexFrame: Deep Reinforcement Learning-Based Pick-and-Place of Objects in Clutter
This research study represents a polydexterous deep reinforcement learning-based pick-
and-place framework for industrial clutter scenarios. In the proposed framework, the agent …
and-place framework for industrial clutter scenarios. In the proposed framework, the agent …
GraspFusionNet: a two-stage multi-parameter grasp detection network based on RGB–XYZ fusion in dense clutter
W Wang, W Liu, J Hu, Y Fang, Q Shao, J Qi - Machine Vision and …, 2020 - Springer
Robotic grasping of diverse range of novel objects is a great challenge in dense clutter,
which is also critical to many applications. However, current methods are vulnerable to …
which is also critical to many applications. However, current methods are vulnerable to …
Object-agnostic suction grasp affordance detection in dense cluster using self-supervised learning. docx
In this paper we study grasp problem in dense cluster, a challenging task in warehouse
logistics scenario. By introducing a two-step robust suction affordance detection method, we …
logistics scenario. By introducing a two-step robust suction affordance detection method, we …
Suction grasping detection for items sorting in warehouse logistics using deep convolutional neural networks
C Zhang, L Zheng, S Pan - 2022 IEEE International …, 2022 - ieeexplore.ieee.org
Items sorting in warehouse logistics is a labor-intensive and time-consuming work.
Combined with computer vision and real-time motion planning technologies, industrial …
Combined with computer vision and real-time motion planning technologies, industrial …