4 citations · 7 across the 7 of their papers we have counts for
5 papers · 1 filter
COSMIK-MPPI: Scaling Constrained Model Predictive Control to Collision Avoidance in Close-Proximity Dynamic Human Environments
Ege Gursoy, Maxime Sabbah, Arthur Haffemayer +5
Ensuring safe physical interaction between torque-controlled manipulators and humans is essential for deploying robots in everyday environments. Model Predictive Control (MPC) has…
Learning-Guided Force-Feedback Model Predictive Control with Obstacle Avoidance for Robotic Deburring
Krzysztof Wojciechowski, Ege Gursoy, Arthur Haffemayer +4
Model Predictive Control (MPC) is widely used for torque-controlled robots, but classical formulations often neglect real-time force feedback and struggle with contact-rich industr…
Toward Global Intent Inference for Human Motion by Inverse Reinforcement Learning
Sarmad Mehrdad, Maxime Sabbah, Vincent Bonnet +1
This paper investigates whether a single, unified cost function can explain and predict human reaching movements, in contrast with existing approaches that rely on subject- or post…
Biomechanically consistent real-time action recognition for human-robot interaction
Wanchen Li, Kahina Chalabi, Sabbah Maxime +5
This paper presents a novel framework for real-time human action recognition in industrial contexts, using standard 2D cameras. We introduce a complete pipeline for robust and real…
Reliability of Single-Level Equality-Constrained Inverse Optimal Control
Filip Bečanović, Kosta Jovanović, Vincent Bonnet
Inverse optimal control (IOC) allows the retrieval of optimal cost function weights, or behavioral parameters, from human motion. The literature on IOC uses methods that are either…