Tianyu Li

Orcid: 0009-0008-7482-6426

Affiliations:
  • University of Pennsylvania, Department of Mechanical Engineering, General Robotics, Automation, Sensing & Perception (GRASP) Lab, Philadelphia, PA, USA


According to our database1, Tianyu Li authored at least 11 papers between 2023 and 2025.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

Online presence:

On csauthors.net:

Bibliography

2025
VLMgineer: Vision Language Models as Robotic Toolsmiths.
CoRR, July, 2025

Elastic Motion Policy: An Adaptive Dynamical System for Robust and Efficient One-Shot Imitation Learning.
CoRR, March, 2025

MORF: Magnetic Origami Reprogramming and Folding System for Repeatably Reconfigurable Structures with Fold Angle Control.
Proceedings of the IEEE International Conference on Robotics and Automation, 2025

2024
Directionality-Aware Mixture Model Parallel Sampling for Efficient Linear Parameter Varying Dynamical System Learning.
IEEE Robotics Autom. Lett., July, 2024

Out-of-Distribution Recovery with Object-Centric Keypoint Inverse Policy For Visuomotor Imitation Learning.
CoRR, 2024

Constraint-Aware Intent Estimation for Dynamic Human-Robot Object Co-Manipulation.
Proceedings of the Robotics: Science and Systems XX, 2024

Constrained Passive Interaction Control: Leveraging Passivity and Safety for Robot Manipulators.
Proceedings of the IEEE International Conference on Robotics and Automation, 2024

Learning Complex Motion Plans using Neural ODEs with Safety and Stability Guarantees.
Proceedings of the IEEE International Conference on Robotics and Automation, 2024

2023
DAMM: Directionality-Aware Mixture Model Parallel Sampling for Efficient Dynamical System Learning.
CoRR, 2023

Learning Safe and Stable Motion Plans with Neural Ordinary Differential Equations.
CoRR, 2023

Task Generalization with Stability Guarantees via Elastic Dynamical System Motion Policies.
Proceedings of the Conference on Robot Learning, 2023


  Loading...