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Hsiu-chin Lin

17 accepted papers

2026

Contractive Diffusion Policies: Robust Action Diffusion via Contractive Score-Based Sampling with Differential Equations

Amin Abyaneh, Charlotte Morissette, Mohamad H. Danesh, Anas Houssaini, David Meger, Gregory Dudek +1
ICLR 2026poster

Diffusion policies have emerged as powerful generative models for offline policy learning, whose sampling process can be rigorously characterized by a score function guiding a Stochastic Differential Equation (SDE). However, the same score-based SDE modeling that grants diffusion policies the flexib…

Cited by 0Source ↗Scholar ↗
2026

SAD-Flower: Flow Matching for Safe, Admissible, and Dynamically Consistent Planning

Tzu-Yuan Huang, Armin Lederer, Dai-Jie Wu, Xiaobing Dai, Sihua Zhang, Hsiu-Chin Lin +3
ICML 2026poster

Flow matching (FM) has shown promising results in data-driven planning. However, it inherently lacks formal guarantees for ensuring state and action constraints, whose satisfaction is a fundamental and crucial requirement for the safety and admissibility of planned trajectories on various systems. M…

Cited by 0Source ↗code ↗Scholar ↗
2026

VOCALoco: Viability-Optimized Cost-Aware Adaptive Locomotion

Stanley Wu, Mohamad H. Danesh, Simon Li, Hanna Yurchyk, Amin Abyaneh, Anas El Houssaini +2
RA-L 2026

Recent advancements in legged robot locomotion have facilitated traversal over increasingly complex terrains. Despite this progress, many existing approaches rely on end-to-end deep reinforcement learning (DRL), which poses limitations in terms of safety and interpretability, especially when general

Cited by 1Source ↗Scholar ↗
2026

VOCALoco: Viability-Optimized Cost-Aware Adaptive Locomotion

Stanley Wu, Mohamad Hosein Danesh, Simon Li, Hanna Yurchyk, Amin Abyaneh, Anas El Houssaini +2
ICRA 2026poster

Recent advancements in legged robot locomotion have facilitated traversal over increasingly complex terrains. Despite this progress, many existing approaches rely on end- to-end deep reinforcement learning (DRL), which poses limi- tations in terms of safety and interpretability, especially when gene…

Cited by 0Source ↗PDF ↗Scholar ↗
2025

Contractive Dynamical Imitation Policies for Efficient Out-of-Sample Recovery

Amin Abyaneh, Mahrokh Ghoddousi Boroujeni, Hsiu-Chin Lin, Giancarlo Ferrari-Trecate
ICLR 2025poster

Imitation learning is a data-driven approach to learning policies from expert behavior, but it is prone to unreliable outcomes in out-of-sample (OOS) regions. While previous research relying on stable dynamical systems guarantees convergence to a desired state, it often overlooks transient behavior.…

Cited by 2Source ↗PDF ↗code ↗Scholar ↗
2021

Online Dynamic Trajectory Optimization and Control for a Quadruped Robot

Oguzhan Cebe, Carlo Tiseo, Guiyang Xin, Hsiu-chin Lin, Joshua Smith, Michael Mistry
ICRA 2021poster

Legged robot locomotion requires the planning of stable reference trajectories, especially while traversing uneven terrain. The proposed trajectory optimization framework is capable of generating dynamically stable base and footstep trajectories for multiple steps. The locomotion task can be defined…

Cited by 33Source ↗Scholar ↗
2020

Bounded haptic teleoperation of a quadruped robot’s foot posture for sensing and manipulation

Guiyang Xin, Joshua Smith, David Rytz, Wouter Wolfslag, Hsiu-Chin Lin, Michael Mistry
ICRA 2020poster

This paper presents a control framework to teleoperate a quadruped robot's foot for operator-guided haptic exploration of the environment. Since one leg of a quadruped robot typically only has 3 actuated degrees of freedom (DoFs), the torso is employed to assist foot posture control via a hierarchic…

Cited by 16Source ↗Scholar ↗
2019

Single-shot Foothold Selection and Constraint Evaluation for Quadruped Locomotion

Dominik Belter, Jakub Bednarek, Hsiu-Chin Lin, Guiyang Xin, Michael Mistry
ICRA 2019poster

In this paper, we propose a method for selecting the optimal footholds for legged systems. The goal of the proposed method is to find the best foothold for the swing leg on a local elevation map. First, we evaluate the geometrical characteristics of each cell on the elevation map, checks kinematic c…

Cited by 21Source ↗Scholar ↗
2018

A Model-Based Hierarchical Controller for Legged Systems Subject to External Disturbances

Guiyang Xin, Hsiu-Chin Lin, Joshua Smith, Oguzhan Cebe, Michael Mistry
ICRA 2018poster

Legged robots have many potential applications in real-world scenarios where the tasks are too dangerous for humans, and compliance is needed to protect the system against external disturbances and impacts. In this paper, we propose a model-based controller for hierarchical tasks of legged systems s…

Cited by 38Source ↗Scholar ↗
2018

A Projected Inverse Dynamics Approach for Multi-Arm Cartesian Impedance Control

Hsiu-Chin Lin, Joshua Smith, Keyhan Kouhkiloui Babarahmati, Niels Dehio, Michael Mistry
ICRA 2018poster

We propose a model-based control framework for multi-arm manipulation of a rigid object subject to external disturbances. The control framework, based on projected inverse dynamics, decomposes the control law into constrained and unconstrained subspaces. Unconstrained components accomplish the motio…

Cited by 49Source ↗Scholar ↗
2018

Modeling and Control of Multi-Arm and Multi-Leg Robots: Compensating for Object Dynamics During Grasping

Niels Dehio, Joshua Smith, Dennis Leroy Wigand, Guiyang Xin, Hsiu-Chin Lin, Jochen J. Steil +1
ICRA 2018poster

We consider a virtual manipulator in grasping scenarios which allows us to capture the effect of the object dynamics. This modeling approach turns a multi-arm robot into an underactuated system. We observe that controlling floating-base multi-leg robots is fundamentally similar. The Projected Invers…

Cited by 34Source ↗Scholar ↗