Papers
6
Total Citations
60
H-Index
4
About
Isabelle Maroger is a researcher at the forefront of humanoid robotics, specializing in human locomotion modeling and human-robot collaboration. Her work bridges biomechanics and control theory to enable robots to anticipate and adapt to human movement. Maroger’s most cited paper, "Human Trajectory Prediction Model and Its Coupling With a Walking Pattern Generator of a Humanoid Robot" (2021, 27 citations), introduces an optimal control-based framework that allows robots to predict human walking trajectories and proactively adjust their own gait. This contribution is critical for fluid, safe interactions in shared tasks like co-navigation or table handling. Her related work, "Walking Human Trajectory Models and Their Application to Humanoid Robot Locomotion" (18 citations), further develops realistic, computationally efficient models of human gait for real-time robotic use. Maroger has also applied inverse optimal control to decode the underlying objectives of human walking, as seen in her 2021 paper (7 citations). Beyond modeling, she has demonstrated practical integration, performing ICP-based localization experiments on the TALOS humanoid robot. Her research is central to advancing proactive, collaborative robots that can work seamlessly alongside humans.
Research Focus
Key Achievements
Top Papers
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- 3Inverse optimal control to model human trajectories during locomotion7 citations · 2021
- 4ICP Localization and Walking Experiments on a TALOS Humanoid Robot4 citations · 2021
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