Research


Research Interests (Coming Soon!)

My Research mainly focuses on Robot Learning - to enable machines to intelligently interact with the world, improve themselves over time and acquire novel skills via machine learning. Broadly speaking, I study how AI models empower robots to master novel skills or adapt to their environment(i.e. Reinforcement Learning, Imitation Learning, Meta Learning), how AI models are efficiently deployed to improve perception, decision-making, planning, and control capabilities of robots with human-in-the-loop(i.e. Human-Robot Interaction, Human-Robot Collaboration), how multi-modal information can be represented to enhance the sense of presence for human-robot coexistence(i.e. Multimodal LLM). Additionally, my ambition is to work on something COOL, enhancing intelligence for robots (collaborative robots, quadruped robots, humanoid robots, aerial robots, mobile robots, etc.) in real world.

Revolving these goals, my research interests focus on:

  • Robot Learning
  • Robotic Perception, Planning, and Control
  • Embodied Multimodal Intelligence in Robotics
  • Simultaneous Localization and Mapping (SLAM)
  • Autonomous Driving

Research Experience

Learning Task-Focused Deep Visuomotor Policies for Multimodal Astronaut-Robot Collaborative Manipulation

Chuanke Pang, Rui Zhong
International Astronautical Congress (IAC) 2024
Webpage  •   PDF  •   Code

Design and Experiment of On-Orbit Assembly Ground Simulation Robot

Chuanke Pang, Rui Zhong
International Conference on Mechanical, Electric, and Industrial Engineering (MEIE) 2022
Webpage  •   Paper  •   Code

TROID: A Space-Oriented Multi-Task Robot Manipulation Dataset

Chuanke Pang, Rui Zhong
Chinese Aerospace Control Conference (CACC) 2024
Webpage  •   PDF  •   Code

High Precision Assembly with Dual-Arm Collaborative Robot Based on the Fusion of Vision and Force-Haptics

Chuanke Pang, Rui Zhong
Chinese Aerospace Control Conference (CACC) 2022
Webpage  •   PDF  •   Code