Learning suction graspability considering grasp quality and robot reachability for bin-picking
P Jiang, J Oaki, Y Ishihara, J Ooga, H Han… - Frontiers in …, 2022 - frontiersin.org
Deep learning has been widely used for inferring robust grasps. Although human-labeled
RGB-D datasets were initially used to learn grasp configurations, preparation of this kind of …
RGB-D datasets were initially used to learn grasp configurations, preparation of this kind of …
MetaGraspNetV2: All-in-one dataset enabling fast and reliable robotic bin picking via object relationship reasoning and dexterous grasping
Grasping unknown objects in unstructured environments is one of the most challenging and
demanding tasks for robotic bin picking systems. Developing a holistic approach is crucial to …
demanding tasks for robotic bin picking systems. Developing a holistic approach is crucial to …
Metagraspnet: A large-scale benchmark dataset for scene-aware ambidextrous bin picking via physics-based metaverse synthesis
Autonomous bin picking poses significant challenges to vision-driven robotic systems given
the complexity of the problem, ranging from various sensor modalities, to highly entangled …
the complexity of the problem, ranging from various sensor modalities, to highly entangled …