Cheongjae Jang

About

Cheongjae Jang is a leading researcher in robot dynamics and control, with a particular focus on geometric methods and bio-inspired motion planning. His major contributions lie in advancing the application of differential geometry and Lie group theory to robot dynamics, most notably through his highly cited tutorial review, "Geometric Algorithms for Robot Dynamics: A Tutorial Review" (55 citations), which has become a key reference for the field. Jang has also made significant strides in human-like robot control, proposing a stochastic optimal feedback control law for generating natural arm movements, inspired by the minimum variance principle. His work extends to the challenging domain of continuum robotics, where he has developed mechanics-based kinematic models for on-line parameter estimation of concentric tube robots. Additionally, Jang has explored attention-based control strategies for dynamic tasks such as ball catching. With a research portfolio that bridges rigorous mathematical foundations and practical robotic applications, Jang’s work continues to influence both the theory and implementation of advanced robotic systems.

Research Focus

Key Achievements

Top Papers

1. 1
   Geometric Algorithms for Robot Dynamics: A Tutorial Review

   55 citations · 2018
2. 2
   Kinematic feedback control laws for generating natural arm movements

   9 citations · 2013
3. 3
   Toward on-line parameter estimation of concentric tube robots using a mechanics-based kinematic model

   7 citations · 2016
4. 4
   Closure to “Discussion of ‘Geometric Algorithms for Robot Dynamics: A Tutorial Review'” (Park, F. C., Kim, B., Jang, C., and Hong, J., 2018, ASME Appl. Mech. Rev., 70(1), p. 010803)

   3 citations · 2018
5. 5
   A Minimum Attention Control Law for Ball Catching

   2 citations · 2014

Key Collaborators

Contact & Links