Research
Publications
[1] Zhang, C., Chen, J., Li, J., Peng, Y., & Mao, Z. (2023). Large language models for human-robot interaction: A review. Biomimetic Intelligence and Robotics, 100131. (Paper link)
[2] Zhang, C., Meng, X., Qi, D., & Chirikjian, G. S. (2024). RAIL: Robot Affordance Imagination with Large Language Models. arXiv preprint arXiv:2403.19369.(Under review of IROS 2024)(Arxiv link)
[3] Peng, Y., Zhang, C., Hu, C., & Mao, Z. (2024). Integration of Large Language Models in Control of EHD Pumps for Precise Color Synthesis. arXiv preprint arXiv:2401.11500.(Arxiv link)
Projects
(1) RAIL: Robot Affordance Imagination with Large Language Models
- An affordance reasoning pipeline that only requests target affordance names.
- An imagination framework simulates customized profiles for multi-class affordances.
- A real robot manipulation system for performing novel tasks on unseen objects based on affordance reasoning.
(2) Learning to kick: Non-prehensile manipulation for quadruped robots.
- Generation of kicking motion: An effective MPC-based controller applied.
- Data fitting model: Used for making predictions on motion parameters.
- Continuous navigation: A locomotion controller trained by RL for reaching goal.
(3) Investigation on reinforcement learning in hand robot manipulation.
- Exploration in RL task environment settings.
- Performance comparison between different RL algorithms.
- Investigation on hyperparameter sittings and reward functions.
- Effects of parallel training.
(4) Reinforcement learning for underwater robot control. [github repo]
- Design of RL training environment for robot.
- Implementation of multiple RL algorithms and performance comparison.
(4) SLAM and path planning for automatic nagavition of mobile vehicles. [github repo]
- Implementation of SLAM and path planning algorithms.
- Simulation environment of obstacles in physical environments