24 citations · 70 across the 16 of their papers we have counts for
19 papers
In-Context Learning World Models for Robot Dual-Arm Manipulation of Soft Garment with Partial Observations
Hengyi Sim, Quentin Rouxel, Dennis Hong +2
Robust manipulation of soft objects, such as garments, is a critical skill for service and household robots to adopt, but remains challenging due to its high-dimensional state spac…
Reasoning Without Inference Cost: Latent Semantic Scaffolding for Robot VLA Policies
Andrew Ting Yan Li, Zhuo Li, Zhelin Yang +3
Vision-language-action (VLA) models are trained by imitation and capture what action to take but not why; adding causal reasoning improves manipulation, but current methods pay for…
Beyond Point-Attached Semantics: Stable Object-Centric Semantic Fields for Robust Manipulation
Zheng Sun, Lerong Zhang, Zhihao Li +3
Robotic manipulation often requires identifying functional parts, such as a mug handle or a hammer head. However, features attached to observed 3D points can vary with viewpoint an…
Transferability Through Cooperative Competitions
Rodrigo Serra, Carlos Azevedo, André Silva +6
This paper presents a novel framework for cooperative robotics competitions (coopetitions) that promote the transferability and composability of robotics modules, including softwar…
Adapt as You Say: Online Interactive Bimanual Skill Adaptation via Human Language Feedback
Zhuo Li, Dianxi Li, Tao Teng +5
Developing general-purpose robots capable of autonomously operating in human living environments requires the ability to adapt to continuously evolving task conditions. However, ad…
CaFe-TeleVision: A Coarse-to-Fine Teleoperation System with Immersive Situated Visualization for Enhanced Ergonomics
Zixin Tang, Yiming Chen, Quentin Rouxel +3
Teleoperation presents a promising paradigm for remote control and robot proprioceptive data collection. Despite recent progress, current teleoperation systems still suffer from li…
Towards Deploying VLA without Fine-Tuning: Plug-and-Play Inference-Time VLA Policy Steering via Embodied Evolutionary Diffusion
Zhuo Li, Junjia Liu, Zhipeng Dong +4
Vision-Language-Action (VLA) models have demonstrated significant potential in real-world robotic manipulation. However, pre-trained VLA policies still suffer from substantial perf…
Extremum Flow Matching for Offline Goal Conditioned Reinforcement Learning
Quentin Rouxel, Clemente Donoso, Fei Chen +2
Imitation learning is a promising approach for enabling generalist capabilities in humanoid robots, but its scaling is fundamentally constrained by the scarcity of high-quality exp…
From Vocal Instructions to Household Tasks: The Inria TIAGo++ in the euROBIN Service Robots Coopetition
Fabio Amadio, Clemente Donoso, Dionis Totsila +6
This paper describes the Inria team's integrated robotics system used in the 1st euROBIN coopetition, during which service robots performed voice-activated household tasks in a kit…
Words2Contact: Identifying Support Contacts from Verbal Instructions Using Foundation Models
Dionis Totsila, Quentin Rouxel, Jean-Baptiste Mouret +1
This paper presents Words2Contact, a language-guided multi-contact placement pipeline leveraging large language models and vision language models. Our method is a key component for…
Flow Matching Imitation Learning for Multi-Support Manipulation
Quentin Rouxel, Andrea Ferrari, Serena Ivaldi +1
Humanoid robots could benefit from using their upper bodies for support contacts, enhancing their workspace, stability, and ability to perform contact-rich and pushing tasks. In th…
Multi-Contact Whole-Body Force Control for Position-Controlled Robots
Quentin Rouxel, Serena Ivaldi, Jean-Baptiste Mouret
Many humanoid and multi-legged robots are controlled in positions rather than in torques, which prevents direct control of contact forces, and hampers their ability to create multi…
Feasibility Retargeting for Multi-contact Teleoperation and Physical Interaction
Quentin Rouxel, Ruoshi Wen, Zhibin Li +3
This short paper outlines two recent works on multi-contact teleoperation and the development of the SEIKO (Sequential Equilibrium Inverse Kinematic Optimization) framework. SEIKO…
Achieving Dexterous Bidirectional Interaction in Uncertain Conditions for Medical Robotics
Carlo Tiseo, Quentin Rouxel, Martin Asenov +4
Medical robotics can help improve and extend the reach of healthcare services. A major challenge for medical robots is the complex physical interaction between the robot and the pa…
Multi-Contact Motion Retargeting using Whole-body Optimization of Full Kinematics and Sequential Force Equilibrium
Quentin Rouxel, Kai Yuan, Ruoshi Wen +1
This paper presents a multi-contact motion adaptation framework that enables teleoperation of high degree-of-freedom (DoF) robots, such as quadrupeds and humanoids, for loco-manipu…
Collaborative Bimanual Manipulation Using Optimal Motion Adaptation and Interaction Control
Ruoshi Wen, Quentin Rouxel, Michael Mistry +2
This work developed collaborative bimanual manipulation for reliable and safe human-robot collaboration, which allows remote and local human operators to work interactively for bim…
Fine Manipulation and Dynamic Interaction in Haptic Teleoperation
Carlo Tiseo, Quentin Rouxel, Zhibin Li +1
The teleoperation of robots enables remote intervention in distant and dangerous tasks without putting the operator in harm's way. However, remote operation faces fundamental chall…
Robust Impedance Control for Dexterous Interaction Using Fractal Impedance Controller with IK-Optimisation
Carlo Tiseo, Quentin Rouxel, Zhibin Li +1
Robust dynamic interactions are required to move robots in daily environments alongside humans. Optimisation and learning methods have been used to mimic and reproduce human moveme…
Robust High-Transparency Haptic Exploration for Dexterous Telemanipulation
Keyhan Kouhkiloui Babarahmati, Carlo Tiseo, Quentin Rouxel +2
Robotic teleoperation will allow us to perform complex manipulation tasks in dangerous or remote environments, such as needed for planetary exploration or nuclear decommissioning.…