Celine Chibani
Papers
1
Total Citations
2
H-Index
1
About
Celine Chibani is a robotics researcher whose work sits at the intersection of human-robot interaction, sensor fusion, and autonomous locomotion. Her primary focus is on enhancing the perceptual and decision-making capabilities of bipedal robots, particularly in unstructured environments. Her most cited work, "Human-Aided Online Terrain Classification for Bipedal Robots Using Augmented Reality" (2022), introduces a novel framework that leverages augmented reality to enable real-time, human-in-the-loop terrain classification. By fusing data from force, position, current, and inertial sensors on the NAO humanoid robot, Chibani’s system allows robots to adapt their gait and control strategies on the fly, significantly improving stability and safety in dynamic settings. This contribution is foundational for advancing autonomous navigation in humanoid robotics, bridging the gap between human intuition and machine learning. Though early in her career, her work has already garnered attention for its practical approach to real-world deployment, and she continues to push the boundaries of how robots perceive and interact with their surroundings.
Research Focus
Key Achievements
Top Papers
- 1