From the 1 of 6 linked papers with an AI index.
6 papers
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
The paper presents Acc-CBF-QP, an acceleration-based quadratic program safety filter that enforces control barrier function constraints on any reinforcement‑learning policy at runt…
QP-Based Control of an Underactuated Aerial Manipulator under Constraints
Nesserine Laribi, Mohammed Rida Mokhtari, Abdelaziz Benallegue +2
This paper presents a constraint-aware control framework for underactuated aerial manipulators, enabling accurate end-effector trajectory tracking while explicitly accounting for s…
Humanoid Loco-Manipulations Pattern Generation and Stabilization Control
Masaki Murooka, Kevin Chappellet, Arnaud Tanguy +5
In order for a humanoid robot to perform loco-manipulation such as moving an object while walking, it is necessary to account for sustained or alternating external forces other tha…
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…
Robust Humanoid Walking on Compliant and Uneven Terrain with Deep Reinforcement Learning
Rohan P. Singh, Mitsuharu Morisawa, Mehdi Benallegue +2
For the deployment of legged robots in real-world environments, it is essential to develop robust locomotion control methods for challenging terrains that may exhibit unexpected de…
Humanoid Robot RHP Friends: Seamless Combination of Autonomous and Teleoperated Tasks in a Nursing Context
Mehdi Benallegue, Guillaume Lorthioir, Antonin Dallard +15
This paper describes RHP Friends, a social humanoid robot developed to enable assistive robotic deployments in human-coexisting environments. As a use-case application, we present…