4 citations · 9 across the 7 of their papers we have counts for
8 papers
Toward Trustworthy Physical AI for Human Interaction
Niccolò Pagliarani, Maximilian Stölzle, Cosima du Pasquier +6
Robots are entering human spaces faster than we can establish when they deserve trust. We propose a framework for trustworthy physical AI that integrates Safety, Behavioral Intelli…
Safe Execution of RL Policies Via Acceleration-Based CBF-QP Constraint Enforcement for Real-World Robotic Deployments
Bastien Muraccioli, Alice Cariou, Pierre-Alexandre Leziart +4
Reinforcement Learning (RL) has demonstrated remarkable capabilities for solving complex robotic control problems, but its lack of safety guarantees severely limits deployment on h…
Driving Style Recognition Like an Expert Using Semantic Privileged Information from Large Language Models
Zhaokun Chen, Chaopeng Zhang, Xiaohan Li +3
Existing driving style recognition systems largely depend on low-level sensor-derived features for training, neglecting the rich semantic reasoning capability inherent to human exp…
Adaptive Wiping: Adaptive contact-rich manipulation through few-shot imitation learning with Force-Torque feedback and pre-trained object representations
Chikaha Tsuji, Enrique Coronado, Pablo Osorio +1
Imitation learning offers a pathway for robots to perform repetitive tasks, allowing humans to focus on more engaging and meaningful activities. However, challenges arise from the…
Demonstrating a Control Framework for Physical Human-Robot Interaction Toward Industrial Applications
Bastien Muraccioli, Mathieu Celerier, Mehdi Benallegue +1
Physical Human-Robot Interaction (pHRI) is critical for implementing Industry 5.0, which focuses on human-centric approaches. However, few studies explore the practical alignment o…
Tactile-based Active Inference for Force-Controlled Peg-in-Hole Insertions
Tatsuya Kamijo, Ixchel G. Ramirez-Alpizar, Enrique Coronado +1
Reinforcement Learning (RL) has shown great promise for efficiently learning force control policies in peg-in-hole tasks. However, robots often face difficulties due to visual occl…
Aligning Robot's Behaviours and Users' Perceptions Through Participatory Prototyping
Pamela Carreno-Medrano, Leimin Tian, Aimee Allen +6
Robots are increasingly being deployed in public spaces. However, the general population rarely has the opportunity to nominate what they would prefer or expect a robot to do in th…
Node Primitives: an open end-user programming platform for social robots
Enrique Coronado, Fulvio Mastrogiovanni, Gentiane Venture
With the expected adoption of robots able to seamlessly and intuitively interact with people in real-world scenarios, the need arises to provide non-technically-skilled users with…