22 citations · 24 across the 2 of their papers we have counts for
9 papers · 1 filter
DexDiff: Towards Extrinsic Dexterity Manipulation of Ungraspable Objects in Unrestricted Environments
Chengzhong Ma, Houxue Yang, Hanbo Zhang +5
Grasping large and flat objects (e.g. a book or a pan) is often regarded as an ungraspable task, which poses significant challenges due to the unreachable grasping poses. Previous…
Robotic Grasping from Classical to Modern: A Survey
Hanbo Zhang, Jian Tang, Shiguang Sun +1
Robotic Grasping has always been an active topic in robotics since grasping is one of the fundamental but most challenging skills of robots. It demands the coordination of robotic…
Density-based Curriculum for Multi-goal Reinforcement Learning with Sparse Rewards
Deyu Yang, Hanbo Zhang, Xuguang Lan +1
Multi-goal reinforcement learning (RL) aims to qualify the agent to accomplish multi-goal tasks, which is of great importance in learning scalable robotic manipulation skills. Howe…
REGNet: REgion-based Grasp Network for End-to-end Grasp Detection in Point Clouds
Binglei Zhao, Hanbo Zhang, Xuguang Lan +3
Reliable robotic grasping in unstructured environments is a crucial but challenging task. The main problem is to generate the optimal grasp of novel objects from partial noisy obse…
A Real-time Robotic Grasp Approach with Oriented Anchor Box
Hanbo Zhang, Xinwen Zhou, Xuguang Lan +3
Grasp is an essential skill for robots to interact with humans and the environment. In this paper, we build a vision-based, robust and real-time robotic grasp approach with fully c…
A Multi-task Convolutional Neural Network for Autonomous Robotic Grasping in Object Stacking Scenes
Hanbo Zhang, Xuguang Lan, Site Bai +3
Autonomous robotic grasping plays an important role in intelligent robotics. However, how to help the robot grasp specific objects in object stacking scenes is still an open proble…