Charbel Abi Hana

Papers

1

Total Citations

1

H-Index

1

About

Charbel Abi Hana is a robotics researcher whose work sits at the intersection of autonomous navigation, human-robot interaction, and imitation learning. His primary research focus is on making path planning for Autonomous Mobile Robots (AMRs) more intuitive and accessible by leveraging human input through natural modalities like sketching. In his most cited work, "End-to-end Sketch-Guided Path Planning through Imitation Learning for Autonomous Mobile Robots" (2025), Abi Hana tackles a fundamental challenge: enabling robots to follow human-drawn paths without relying on complex reward functions or expensive sensor setups. By developing an end-to-end imitation learning framework that translates freehand sketches directly into robot trajectories, he offers a more flexible and user-friendly alternative to traditional path planning methods. This approach has the potential to democratize robot programming, allowing non-experts to guide AMRs in dynamic environments. While still early in his career, his work has already garnered attention for its practical implications in warehouse logistics, service robotics, and assistive technologies. Abi Hana’s contributions are paving the way for more natural human-robot collaboration, where communication happens through simple gestures rather than code.

Research Focus

Key Achievements

1
H-Index
1
Papers
1
Total Citations
1
Avg Citations/Paper
🏆 Most Cited Paper
End-to-end Sketch-Guided Path Planning through Imitation Learning for Autonomous Mobile Robots
1 citations · 2025
📈 Most Prolific Year: 2025 (1 Papers)
🤝 Key Collaborators: 3

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago