H. J. Terry Suh — accepted AI-conference papers

2025

Is Linear Feedback on Smoothed Dynamics Sufficient for Stabilizing Contact-Rich Plans?

Yuki Shirai, Tong Zhao, H. J. Terry Suh, Huaijiang Zhu, Xinpei Ni, Jiuguang Wang +2

ICRA 2025

Designing planners and controllers for contact-rich manipulation is extremely challenging as contact violates the smoothness conditions that many gradient-based controller synthesis tools assume. Contact smoothing approximates a non-smooth system with a smooth one, allowing one to use these synthesi

Cited by 10 Source ↗Scholar ↗

2020

Energy-Efficient Motion Planning for Multi-Modal Hybrid Locomotion

H. J. Terry Suh, Xiaobin Xiong, Andrew Singletary, Aaron D. Ames, Joel W. Burdick

IROS 2020poster

Hybrid locomotion, which combines multiple modalities of locomotion within a single robot, enables robots to carry out complex tasks in diverse environments. This paper presents a novel method for planning multi-modal locomotion trajectories using approximate dynamic programming. We formulate this p…

Cited by 20 Source ↗Scholar ↗