4 citations · 5 across the 12 of their papers we have counts for
12 papers
CNSv2: Probabilistic Correspondence Encoded Neural Image Servo
Anzhe Chen, Hongxiang Yu, Shuxin Li +5
Visual servo based on traditional image matching methods often requires accurate keypoint correspondence for high precision control. However, keypoint detection or matching tends t…
CNS: Correspondence Encoded Neural Image Servo Policy
Anzhe Chen, Hongxiang Yu, Yue Wang +1
Image servo is an indispensable technique in robotic applications that helps to achieve high precision positioning. The intermediate representation of image servo policy is importa…
Learning adaptive manipulation of objects with revolute joint: A case study on varied cabinet doors opening
Hongxiang Yu, Dashun Guo, Zhongxiang Zhou +2
This paper introduces a learning-based framework for robot adaptive manipulating the object with a revolute joint in unstructured environments. We concentrate our discussion on var…
A Hyper-network Based End-to-end Visual Servoing with Arbitrary Desired Poses
Hongxiang Yu, Anzhe Chen, Kechun Xu +4
Recently, several works achieve end-to-end visual servoing (VS) for robotic manipulation by replacing traditional controller with differentiable neural networks, but lose the abili…
Failure-aware Policy Learning for Self-assessable Robotics Tasks
Kechun Xu, Runjian Chen, Shuqi Zhao +5
Self-assessment rules play an essential role in safe and effective real-world robotic applications, which verify the feasibility of the selected action before actual execution. But…
Learning A Simulation-based Visual Policy for Real-world Peg In Unseen Holes
Liang Xie, Hongxiang Yu, Kechun Xu +5
This paper proposes a learning-based visual peg-in-hole that enables training with several shapes in simulation, and adapting to arbitrary unseen shapes in real world with minimal…
Learning to Fill the Seam by Vision: Sub-millimeter Peg-in-hole on Unseen Shapes in Real World
Liang Xie, Hongxiang Yu, Yinghao Zhao +5
In the peg insertion task, human pays attention to the seam between the peg and the hole and tries to fill it continuously with visual feedback. By imitating the human behavior, we…
Electric Vehicle Automatic Charging System Based on Vision-force Fusion
Dashun Guo, Liang Xie, Hongxiang Yu +2
Electric vehicles are an emerging means of transportation with environmental friendliness. The automatic charging is a hot topic in this field that is full of challenges. We introd…
Efficient Object Manipulation to an Arbitrary Goal Pose: Learning-based Anytime Prioritized Planning
Kechun Xu, Hongxiang Yu, Renlang Huang +3
We focus on the task of object manipulation to an arbitrary goal pose, in which a robot is supposed to pick an assigned object to place at the goal position with a specific orienta…
Neural Motion Prediction for In-flight Uneven Object Catching
Hongxiang Yu, Dashun Guo, Huan Yin +4
In-flight objects capture is extremely challenging. The robot is required to complete trajectory prediction, interception position calculation and motion planning in sequence withi…
Learn to Differ: Sim2Real Small Defection Segmentation Network
Zexi Chen, Zheyuan Huang, Yunkai Wang +3
Recent studies on deep-learning-based small defection segmentation approaches are trained in specific settings and tend to be limited by fixed context. Throughout the training, the…
Efficient learning of goal-oriented push-grasping synergy in clutter
Kechun Xu, Hongxiang Yu, Qianen Lai +2
We focus on the task of goal-oriented grasping, in which a robot is supposed to grasp a pre-assigned goal object in clutter and needs some pre-grasp actions such as pushes to enabl…