Vision and Robotics Lab - Institute for Interdisciplinary Information Sciences
The Vision and Robotics Lab at Tsinghua University's Institute for Interdisciplinary Information Sciences focuses on building universal embodied intelligent agents. Research integrates computer vision and reinforcement learning for robotic perception and autonomous decision-making.
Notable achievements
Research in embodied AI, computer vision, and reinforcement learning for robotics
Notable work
Recent publications
All papers →Matched by this lab's specialties (keyword overlap + direct affiliation)
PAEAR: Point Clouds Area Exploration and Active Recognition method driven by reinforcement learning for robotic welding
Yong Tao, Donghua Tan, Fan Ren +6 more
Robotics and Computer-Integrated Manufacturing · 2026
Integrating computer vision and Kalman filter in an assistive system for visually impaired individuals to predict hand-object interaction
Amirmohammad Barsalani, Arman Mardani, Hamidreza Daniali
Robotics and Autonomous Systems · 2026
Multi-pass cutting parameters optimisation with causal reinforcement learning for deformation control of thin-walled parts
Fengyi Lu, Guanghui Zhou, Chao Zhang +2 more
Robotics and Computer-Integrated Manufacturing · 2026
MA2MB: Multi-agent mutual-advising model-based reinforcement learning for pursuit and evasion games
Baolin Zhao, Qi Guo, Xiandong Wang +2 more
Robotics and Autonomous Systems · 2026
Container Unloading via Reinforcement Learning: Picking Order, Deadlock Avoidance, and Proof-of-Concept Simulation
Jan Rüdiger, Max Schenke, Daniel Weber
2026
Learning to Balance Motor Thermal Safety and Quadrupedal Locomotion Performance with Residual Policy
Yuhang Wan, Weixian Lin, Letian Qian +5 more
2026