activity
20182021
most citedA Pushing-Grasping Collaborative Method Based on Deep Q-Network Algorithm in Dual Perspectives

2 citations · 4 across the 5 of their papers we have counts for

collaborators

7 papers

cs.RO2021

A self-supervised learning-based 6-DOF grasp planning method for manipulator

Gang Peng, Zhenyu Ren, Hao Wang +1

To realize a robust robotic grasping system for unknown objects in an unstructured environment, large amounts of grasp data and 3D model data for the object are required, the sizes…

cs.RO20212 cited

A Pushing-Grasping Collaborative Method Based on Deep Q-Network Algorithm in Dual Perspectives

Peng Gang, Liao Jinhu, Guan Shangbin

Aiming at the traditional grasping method for manipulators based on 2D camera, when faced with the scene of gathering or covering, it can hardly perform well in unstructured scenes…

cs.RO20201 cited

A Visual Kinematics Calibration Method for Manipulator Based on Nonlinear Optimization

Peng Gang, Wang Zhihao, Yang Jin +1

The traditional kinematic calibration method for manipulators requires precise three-dimensional measuring instruments to measure the end pose, which is not only expensive due to t…

cs.RO2020

Calibration of the internal and external parameters of wheeled robot mobile chasses and inertial measurement units based on nonlinear optimization

Gang Peng, Zezao Lu, Zejie Tan +2

Mobile robot positioning, mapping, and navigation systems generally employ an inertial measurement unit (IMU) to obtain the acceleration and angular velocity of the robot. However,…

cs.CV20201 cited

Single upper limb pose estimation method based on improved stacked hourglass network

Gang Peng, Yuezhi Zheng, Jianfeng Li +2

At present, most high-accuracy single-person pose estimation methods have high computational complexity and insufficient real-time performance due to the complex structure of the n…

cs.CV2018

Attention to Refine through Multi-Scales for Semantic Segmentation

Shiqi Yang, Gang Peng

This paper proposes a novel attention model for semantic segmentation, which aggregates multi-scale and context features to refine prediction. Specifically, the skeleton convolutio…