activity
20232026
collaborators

11 papers

cs.CV2026

ClothAtlas: Joint Garment Identification and State Estimation under Self-Occlusion

Jens Lundell, Alberta Longhini, Lei Shu +6

Garment manipulation requires inferring both garment identity and complete configuration from partial, self-occluded observations. This creates a chicken-and-egg problem: completin…

cs.RO2026

MoDex: A Diffusion Policy for Sequential Multi-Object Dexterous Grasping

Haofei Lu, Hongjia Liu, Yifei Dong +3

This work addresses sequentially grasping multiple objects with a single dexterous hand without releasing those already held. Most dexterous grasping methods commit all of the hand…

cs.RO2026

Reduced-order Control and Geometric Structure of Learned Lagrangian Latent Dynamics

Katharina Friedl, Noémie Jaquier, Seungyeon Kim +2

Model-based controllers can offer strong guarantees on stability and convergence by relying on physically accurate dynamic models. However, these are rarely available for high-dime…

cs.LG2025

A Non-Adversarial Approach to Idempotent Generative Modelling

Mohammed Al-Jaff, Giovanni Luca Marchetti, Michael C Welle +5

Idempotent Generative Networks (IGNs) are deep generative models that also function as local data manifold projectors, mapping arbitrary inputs back onto the manifold. They are tra…

cs.RO2025

FLoRA: Sample-Efficient Preference-based RL via Low-Rank Style Adaptation of Reward Functions

Daniel Marta, Simon Holk, Miguel Vasco +6

Preference-based reinforcement learning (PbRL) is a suitable approach for style adaptation of pre-trained robotic behavior: adapting the robot's policy to follow human user prefere…

cs.RO2025

Pushing Everything Everywhere All At Once: Probabilistic Prehensile Pushing

Patrizio Perugini, Jens Lundell, Katharina Friedl +1

We address prehensile pushing, the problem of manipulating a grasped object by pushing against the environment. Our solution is an efficient nonlinear trajectory optimization probl…

cs.RO2025

Grasping a Handful: Sequential Multi-Object Dexterous Grasp Generation

Haofei Lu, Yifei Dong, Zehang Weng +3

We introduce the sequential multi-object robotic grasp sampling algorithm SeqGrasp that can robustly synthesize stable grasps on diverse objects using the robotic hand's partial De…

cs.CV2025

Cloth-Splatting: 3D Cloth State Estimation from RGB Supervision

Alberta Longhini, Marcel Büsching, Bardienus P. Duisterhof +4

We introduce Cloth-Splatting, a method for estimating 3D states of cloth from RGB images through a prediction-update framework. Cloth-Splatting leverages an action-conditioned dyna…

cs.LG2024

A Riemannian Framework for Learning Reduced-order Lagrangian Dynamics

Katharina Friedl, Noémie Jaquier, Jens Lundell +2

By incorporating physical consistency as inductive bias, deep neural networks display increased generalization capabilities and data efficiency in learning nonlinear dynamic models…

cs.RO2024

DexDiffuser: Generating Dexterous Grasps with Diffusion Models

Zehang Weng, Haofei Lu, Danica Kragic +1

We introduce DexDiffuser, a novel dexterous grasping method that generates, evaluates, and refines grasps on partial object point clouds. DexDiffuser includes the conditional diffu…

cs.RO2023

CAPGrasp: An Continuous Approach-Constrained Generative Grasp Sampler

Zehang Weng, Haofei Lu, Jens Lundell +1

We propose CAPGrasp, an 6-DoF continuous approach-constrained generative grasp sampler. It includes a novel learning strategy for trai…