Learning to generate 6-dof grasp poses with reachability awareness
X Lou, Y Yang, C Choi, Learning to generate 6-dof grasp poses with reachability awareness, IEEE International Conference on Robotics and Automation (ICRA) 2020, 1532-1538 .
Objective
- Seeking an internship opportunity (Summer 2022) in deep learning, robotics and computer vision related disciplines where I can utilize my knowledge and skills to solve challenging problems.
Education
- Ph.D in Electrical and Computer Engineering, University of Minnesota Twin Cities, expected 2022
- Focused on Deep Learning in Robot Manipulation and Perception, advised by Prof. Changhyun Choi
- GPA 4.0/4.0
- M.S. in Electrical and Computer Engineering, Georgia Institute of Technology, 2015
- GPA 3.5/4.0
- B.S. in Electrical and Computer Engineering, Georgia Institute of Technology, 2014
- Graduated with High Honor
- GPA 3.5/4.0
Work experience
- Application Engineer, dSPACE Inc.
- Developed real-time simulation models for electric vehicles in MATLAB Simulink that suit customers’ needs
- Led in designing and manufacturing of customized dSPACE Hardware-in-Loop (HIL) simulators
- Represented dSPACE in General Motors to participate in the high-performance electric vehicle developments
Research experience
- Research Assistant, University of Minnesota Twin Cities
- Advised by Prof. Changhyun Choi
- Proposed innovative deep learning solutions to challenging problems in 3D robotic manipulation andperception
- Used a Graph Neural Network to learn scene information and grasp novel objects in dense clutters
- Developed a 3DCNN-based 6-DoF robotic grasping system, and extended further to learn collision avoidance
Skills
- Programming: Python, C/C++, MATLAB, MySQL, Git, Bash, Docker, Linux, LaTeX
- Machine Learning: PyTorch, PyTorch-Geometric, Tensorflow, Keras, scikit-learn
- Robotics: Franka Emika Panda, ROS, OpenCV, Open3D, PCL, Gym, MuJoCo, V-REP(CoppeliaSim
Publications
Attribute-Based Robotic Grasping with One-Grasp Adaptation
Yang Yang, Yuanhao Liu, Hengyue Liang, Xibai Lou and Changhyun Choi, Attribute-Based Robotic Grasping with One-Grasp Adaptation, ICRA 2021.
Learning Visual Affordances with Target-Orientated Deep Q-Network to Grasp Objects by Harnessing Environmental Fixtures
Hengyue Liang, Xibai Lou, Yang Yang and Changhyun Choi, Learning Visual Affordances with Target-Orientated Deep Q-Network to Grasp Objects by Harnessing Environmental Fixtures, ICRA 2021.
Collision-Aware Target-Driven Object Grasping in Constrained Environments
X Lou, Y Yang, C Choi, Collision-Aware Target-Driven Object Grasping in Constrained Environments, IEEE International Conference on Robotics and Automation (ICRA) 2021.
Teaching
Service
- Reviewer for ICRA 2021, ICRA 2020
- Reviewer for IROS 2021, IROS 2020