About Me

I am a Ph.D. student at GRASP Lab, University of Pennsylvania, advised by Prof. Nadia Figueroa. I envision a future where robots are not only capable, but also intuitive, adaptive, and safe. My research focuses on enabling robust and efficient motion policy learning, ensuring safe interactions between robots and their physical environments, and promoting engaging human-robot interactions. I am also passionate about designing innovative hardware.

Before coming to Penn, I received my MS in Robotics from Northwestern University and BS in Aerospace Engineering from UIUC.

News

Sep 2025 - I will be at Amazon Robotics working on Vulcan as an intern for Fall 2025.
Jun 2025 - EMP is accepted to IROS 2025.
Jun 2025 - OCR is accepted to IROS 2025.
May 2025 - VLMgineer is accepted to oral @ Workshop on Robot Hardware-Aware Intelligence, RSS 2025.
April 2025 - Presented as a spotlight speaker at the ICRA 2025 Doctoral Consortium.
April 2025 - EMP is accepted as a spotlight paper @ Workshop on Structured Learning, ICRA 2025.
Oct 2024 - OCR is accepted as a spotlight paper @ Workshop on Lifelong Learning for Home Robots, CoRL 2024.
Sep 2024 - Started an internship at Amazon Robotics, Innovation Lab (Westborough, MA).

Research

Flow with the Force Field: Learning 3D Compliant Flow Matching Policies from Force and Demonstration-Guided Simulation Data

{Tianyu Li*, Yihan Li*}, Zizhe Zhang, Nadia Figueroa

Workshop on Contact and Impact-aware Manipulation, IROS 2025

Workshop on Exploring the Role of Energy in Robot Learning and Control, IROS 2025

We introduce a framework for generating force-informed data in simulation, instantiated by a single human demonstration, and show how coupling with a compliant policy improves the performance of a visuomotor policy learned from synthetic data.

VPP-TC: Viability-Preserving Passive Torque Control

{Zizhe Zhang*, Yicong Wang*}, Zhiquan Zhang, Tianyu Li*, Nadia Figueroa

Best Paper Award at Workshop on Exploring the Role of Energy in Robot Learning and Control, IROS 2025

Best Student Paper Award at Workshop on Building Safe Robots, IROS 2025

A quadratic programming-based control framework enforces viability theory constructed constraints on a passive controller tracking a dynamical system, ensuring the robot states remain within the safe set in an infinite time horizon.

VLMgineer: Vision Language Models as Robotic Toolsmiths

{George Jiayuan Gao*, Tianyu Li*}, Junyao Shi, {Yihan Li^†, Zizhe Zhang^†}, Nadia Figueroa, Dinesh Jayaraman

Workshop on Robot Hardware-Aware Intelligence, RSS 2025

We introduce VLMgineer, a novel VLM-driven evolutionary framework that automatically co-design tools and actions to solve robotics task.

Elastic Motion Policy: An Adaptive Dynamical System for Robust and Efficient One-Shot Imitation Learning

Tianyu Li, Sunan Sun, Shubhodeep Shiv Aditya, Nadia Figueroa

IROS 2025

Spotlight Paper in Workshop on Structured Learning for Efficient, Reliable, and Transparent Robots @ ICRA 2025

A one-shot stable imitation learning framework that allows robots to adjust their behavior based on the scene change while respecting the task specification.

MORF: Magnetic Origami Reprogramming and Folding System for Repeatably Reconfigurable Structures with Fold Angle Control

Gabriel Unger, Sridhar Shenoy, Tianyu Li, Nadia Figueroa, Cynthia Sung

ICRA 2025

We introduce MORF, a magnetic origami system enabling repeatedly reprogrammable, rigid structures ideal for adaptive robotic tools.

Out-of-Distribution Recovery with Object-Centric Keypoint Inverse Policy For Visuomotor Imitation Learning

George Jiayuan Gao, Tianyu Li, Nadia Figueroa

IROS 2025

Spotlight Paper in Workshop on Lifelong Learning for Home Robots @ CoRL 2024

A vision-based object-centric recovery policy framework that guides the system back to the training distribution in OOD situations without relying on extra data

Constrained Passive Interaction Control: Leveraging Passivity and Safety for Robot Manipulators

Zhiquan Zhang, Tianyu Li, Nadia Figueroa

ICRA 2024

A novel control architecture that allows a torque-controlled robot to guarantee safety constraints such as kinematic limits, self-collisions, external collisions and singularities and is passive only when feasible

Learning Safe and Stable Motion Plans with Neural Ordinary Differential Equations

Farhad Nawaz, Tianyu Li, Nikolai Matni, Nadia Figueroa

ICRA 2024

This approach learns a motion plan with Neural Ordinary Differential Equations while guaranteeing stability and safety with Control Lyapunov Functions and Control Barrier Functions

Constraint-Aware Intent Estimation for Dynamic Human-Robot Object Co-Manipulation

Yifei Simon Shao, Tianyu Li, Shafagh Keyvanian, Pratik Chaudhari, Vijay Kumar, Nadia Figueroa

RSS 2024

A dynamical system based representation for intent estimation with constraints in human robot co-manipulation tasks

Task Generalization with Stability Guarantees via Elastic Dynamical System Motion Policies

Tianyu Li, Nadia Figueroa

CoRL 2023

A dynamical system based motion policy LfD method with stability guarantees that can generalize to new task configurations without new demonstrations

Directionality-Aware Mixture Model Parallel Sampling for Efficient Linear Parameter Varying Dynamical System Learning

Sunan Sun, Haihui Gao, Tianyu Li, Nadia Figueroa

RA-L

A novel statistical model that applies the Riemannian metric on the n-sphere to efficiently blend non-Euclidean directional data with Euclidean states for learning stable, time-independent motion policies

Past Projects

Planning & Prediction with Human Preference via Deep Inverse Reinforcement Learning

[website]

Using maximum entropy deep IRL to learn agent preference in continuous environment path planning

Using Rethink Sawyer Robot Arm to Play Yoyo

[website]

Developed software and hardware pipeline to play yoyo with visual feedback control on the Sawyer Robot arm

Data-driven Receding Horizon Control with the Koopman Operator

[website]

Performed receding horizon control using data-driven approach with small data in a continuous space