15 citations · 48 across the 15 of their papers we have counts for
16 papers
ARCGym: Benchmarking Deep Reinforcement Learning in Autonomous Robotic Colonoscopy
Guanglin Ji, Martina Finocchiaro, Kenny Erleben +1
Simulations for learning-based autonomous colonoscopic navigation focus mainly on fully actuated capsule robots, failing to capture the contact-rich navigation of long and flexible…
Unfolding the Literature: A Review of Robotic Cloth Manipulation
Alberta Longhini, Yufei Wang, Irene Garcia-Camacho +9
The realm of textiles spans clothing, households, healthcare, sports, and industrial applications. The deformable nature of these objects poses unique challenges that prior work on…
Controllable Motion Synthesis and Reconstruction with Autoregressive Diffusion Models
Wenjie Yin, Ruibo Tu, Hang Yin +3
Data-driven and controllable human motion synthesis and prediction are active research areas with various applications in interactive media and social robotics. Challenges remain i…
Dance Style Transfer with Cross-modal Transformer
Wenjie Yin, Hang Yin, Kim Baraka +2
We present CycleDance, a dance style transfer system to transform an existing motion clip in one dance style to a motion clip in another dance style while attempting to preserve mo…
Back to the Manifold: Recovering from Out-of-Distribution States
Alfredo Reichlin, Giovanni Luca Marchetti, Hang Yin +2
Learning from previously collected datasets of expert data offers the promise of acquiring robotic policies without unsafe and costly online explorations. However, a major challeng…
Geometric Multimodal Contrastive Representation Learning
Petra Poklukar, Miguel Vasco, Hang Yin +3
Learning representations of multimodal data that are both informative and robust to missing modalities at test time remains a challenging problem due to the inherent heterogeneity…
How to Sense the World: Leveraging Hierarchy in Multimodal Perception for Robust Reinforcement Learning Agents
Miguel Vasco, Hang Yin, Francisco S. Melo +1
This work addresses the problem of sensing the world: how to learn a multimodal representation of a reinforcement learning agent's environment that allows the execution of tasks un…
Graph-based Normalizing Flow for Human Motion Generation and Reconstruction
Wenjie Yin, Hang Yin, Danica Kragic +1
Data-driven approaches for modeling human skeletal motion have found various applications in interactive media and social robotics. Challenges remain in these fields for generating…
Graph-based Task-specific Prediction Models for Interactions between Deformable and Rigid Objects
Zehang Weng, Fabian Paus, Anastasiia Varava +3
Capturing scene dynamics and predicting the future scene state is challenging but essential for robotic manipulation tasks, especially when the scene contains both rigid and deform…
Learning Deep Energy Shaping Policies for Stability-Guaranteed Manipulation
Shahbaz Abdul Khader, Hang Yin, Pietro Falco +1
Deep reinforcement learning (DRL) has been successfully used to solve various robotic manipulation tasks. However, most of the existing works do not address the issue of control st…
Enabling Visual Action Planning for Object Manipulation through Latent Space Roadmap
Martina Lippi, Petra Poklukar, Michael C. Welle +4
We present a framework for visual action planning of complex manipulation tasks with high-dimensional state spaces, focusing on manipulation of deformable objects. We propose a Lat…
Learning Stable Normalizing-Flow Control for Robotic Manipulation
Shahbaz Abdul Khader, Hang Yin, Pietro Falco +1
Reinforcement Learning (RL) of robotic manipulation skills, despite its impressive successes, stands to benefit from incorporating domain knowledge from control theory. One of the…
Stability-Guaranteed Reinforcement Learning for Contact-rich Manipulation
Shahbaz A. Khader, Hang Yin, Pietro Falco +1
Reinforcement learning (RL) has had its fair share of success in contact-rich manipulation tasks but it still lags behind in benefiting from advances in robot control theory such a…
Latent Space Roadmap for Visual Action Planning of Deformable and Rigid Object Manipulation
Martina Lippi, Petra Poklukar, Michael C. Welle +4
We present a framework for visual action planning of complex manipulation tasks with high-dimensional state spaces such as manipulation of deformable objects. Planning is performed…
Data-efficient Model Learning and Prediction for Contact-rich Manipulation Tasks
Shahbaz Abdul Khader, Hang Yin, Pietro Falco +1
In this letter, we investigate learning forward dynamics models and multi-step prediction of state variables (long-term prediction) for contact-rich manipulation. The problems are…
StableNet: Semi-Online, Multi-Scale Deep Video Stabilization
Chia-Hung Huang, Hang Yin, Yu-Wing Tai +1
Video stabilization algorithms are of greater importance nowadays with the prevalence of hand-held devices which unavoidably produce videos with undesirable shaky motions. In this…