4 papers
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…
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…
Learning Human Reaching Optimality Principles from Minimal Observation Inverse Reinforcement Learning
Sarmad Mehrdad, Maxime Sabbah, Vincent Bonnet +1
This paper investigates the application of Minimal Observation Inverse Reinforcement Learning (MO-IRL) to model and predict human arm-reaching movements with time-varying cost weig…