5 papers
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…
ROI-based Robotic Grasp Detection for Object Overlapping Scenes
Hanbo Zhang, Xuguang Lan, Site Bai +3
Grasp detection with consideration of the affiliations between grasps and their owner in object overlapping scenes is a necessary and challenging task for the practical use of the…
Fully Convolutional Grasp Detection Network with Oriented Anchor Box
Xinwen Zhou, Xuguang Lan, Hanbo Zhang +3
In this paper, we present a real-time approach to predict multiple grasping poses for a parallel-plate robotic gripper using RGB images. A model with oriented anchor box mechanism…
Visual Manipulation Relationship Network
Hanbo Zhang, Xuguang Lan, Xinwen Zhou +3
Robotic grasping detection is one of the most important fields in robotics, in which great progress has been made recent years with the help of convolutional neural network (CNN).…