Chengnan (Jimmy) Shentu is a Ph.D. student of 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

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

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

arXiv preprint arXiv:2409.09970, 2024.

DOI Link
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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
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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.