Jimmy Shentu

Chengnan (Jimmy) Shentu is a Ph.D. candidate in Computer Science at the University of Toronto. His research interests are modeling and control for continuum robots.

Before joining CRL as a Ph.D. Student in September 2022, Jimmy completed his undergraduate thesis with the lab. Jimmy obtained his B.A.Sc. in Engineering Science majoring in Robotics and minoring in Artificial Intelligence from the University of Toronto in April 2022 with honours.

Publications

Automating Tension Calibration for Tendon-Driven Continuum Robots: A Low-Cost Approach Towards Consistent Teleoperation

Kyum Lee, Chengnan Shentu, Chloe Pogue, Jessica Burgner-Kahrs

IEEE International Conference on Robotics and Automation [accepted], 2025.

A Non-Linear Model Predictive Task-Space Controller Satisfying Shape Constraints for Tendon-Driven Continuum Robots

Maximilian Hachen, Chengnan Shentu, Sven Lilge, Jessica Burgner-Kahrs

IEEE Robotics and Automation Letters, 10(3):2438-2445, 2025.

DOI Link

A Non-Linear Model Predictive Task-Space Controller Satisfying Shape Constraints for Tendon-Driven Continuum Robots

Maximilian Hachen, Chengnan Shentu, Sven Lilge, Jessica Burgner-Kahrs

IEEE International Conference on Robotics and Automation, Late Breaking News Poster, 2024.

Open Continuum Robotics - One Actuation Module to Create them All

Reinhard M. Grassmann, Chengnan Shentu, Taqi Hamoda, Puspita Triana Dewi, Jessica Burgner-Kahrs

Frontiers in Robotics and AI, 11, 2024.

DOI GitHub Video

MoSS - Monocular Shape Sensing for Continuum Robots.

Chengnan Shentu, Enxu Li, Chaojun Chen, Puspita Triana Dewi, David B. Lindell, Jessica Burgner-Kahrs

IEEE Robotics and Automation Letters, 9(2):1524 - 1531, 2024.

DOI GitHub

Universal-jointed Tendon-driven Continuum Robot - Design, Kinematic Modeling, and Locomotion in Narrow Tubes

Chengnan Shentu, Jessica Burgner-Kahrs

40th Anniversary of the IEEE International Conference on Robotics and Automation, 2024.

DOI Link