Robot Learning and Control Lab

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Robot learning research in the RLC Lab

Robot Learning and Control Lab

At RLC Lab, we advance research in reinforcement learning, robot learning, and AI-based optimization. Our mission is to enable more intelligent autonomous robotic systems through advanced learning and control algorithms

Latest Publications

All publications
  1. 2026-10Journal

    Efficient knowledge distillation with emphasized Radon features for wafer bin map classification

    Sanghyun Ryoo, Jangwon Kim, Jaehyung Cho, Jongyul Lee, Junkee Hong, Soohee Han

    Engineering Applications of Artificial Intelligence, 181. 115299

    Paper (opens in a new tab)
  2. 2026-03Journal

    Giving Autonomy to Empty-Headed Robots: Design and Deployment Challenges

    Hoyong Lee, Inveom Kwak, Chiwon Sung, Hakjun Lee, Jangwon Kim, Youngtae Moon, Soo Jeon, Kwang Y. Lee, Soohee Han

    Journal of Field Robotics, 43, 3452–3473

    Paper (opens in a new tab)
  3. 2026-02Journal

    Bayesian policy distillation: Towards lightweight and fast neural policy networks

    Jangwon Kim, Yoonsu Jang, Jonghyeok Park, Yoonhee Gil, Soohee Han

    Engineering Applications of Artificial Intelligence, 166, 113539

    Paper (opens in a new tab)Code (opens in a new tab)

Latest news

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  1. Lab

    [정보통신기획평가원] AI반도체 융합전공 학∙석사 연계과정 과제 참여

  2. Lab

    RLC Lab 홈페이지 개설