Cognitive Learning for Vision and Robotics (CLVR) Lab
Led by Joseph J. Lim at KAIST, CLVR develops intelligent robotic systems that make sequential decisions through perception, action, and reasoning. The lab focuses on reinforcement learning, world models with representation learning, visual perception, and symbolic manipulation.
Notable achievements
Research in embodied AI and robot learning; development of world models for robotics
Notable work
Recent publications
All papers →Matched by this lab's specialties (keyword overlap + direct affiliation)
Towards embodied AI in manufacturing: Review, Evaluation, and Future directions
Yexing Zheng, Zhengyang Ling, Qinghua Wang +5 more
Robotics and Computer-Integrated Manufacturing · 2027
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
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
Feasibility-Aware Security-Constrained Unit Commitment via Hybrid Soft Actor-Critic with Quantum-Sampled Features
George Dimas, Amin Masoumi, Mert Korkali
2026
HOLO-MPPI: Multi-Scenario Motion Planning via Hierarchical Policy Optimization
Youngjae Min, Jovin D'sa, Faizan M. Tariq +3 more
2026