Maxime Sabbah

According to our database1, Maxime Sabbah authored at least 11 papers between 2023 and 2026.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

On csauthors.net:

Bibliography

2026
COSMIK-MPPI: Scaling Constrained Model Predictive Control to Collision Avoidance in Close-Proximity Dynamic Human Environments.
CoRR, April, 2026

Toward Global Intent Inference for Human Motion by Inverse Reinforcement Learning.
CoRR, March, 2026

2025
Learning Human Reaching Optimality Principles from Minimal Observation Inverse Reinforcement Learning.
CoRR, October, 2025

Optimal Motion Prediction for Human-to-Robot Handovers.
Proceedings of the IEEE International Conference on Robotics and Biomimetics, 2025

Biomechanically Consistent Real-Time Action Recognition for Human-Robot Interaction.
Proceedings of the IEEE International Conference on Robotics and Biomimetics, 2025

Minimal Observations Inverse Reinforcement Learning for Predicting Human Box-Lifting Motions.
Proceedings of the 24th IEEE-RAS International Conference on Humanoid Robots, 2025

2024
Lower Limbs 3D Joint Kinematics Estimation From Force Plates Data and Machine Learning.
Proceedings of the 23rd IEEE-RAS International Conference on Humanoid Robots, 2024

Ground Reaction Forces and Moments Estimation from Embedded Insoles using Machine Learning Regression Models.
Proceedings of the 10th IEEE RAS/EMBS International Conference for Biomedical Robotics and Biomechatronics, 2024

Lower Limbs Human Motion Estimation from Sparse Multi-Modal Measurements.
Proceedings of the 10th IEEE RAS/EMBS International Conference for Biomedical Robotics and Biomechatronics, 2024

2023
Multi-Modal Upper Limbs Human Motion Estimation from a Reduced Set of Affordable Sensors.
IROS, 2023

FIGAROH: A Python Toolbox for Dynamic Identification and Geometric Calibration of Robots and Humans.
Proceedings of the 22nd IEEE-RAS International Conference on Humanoid Robots, 2023


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