Aref Hebri
Papers
2
Total Citations
8
H-Index
2
About
Aref Hebri is a robotics researcher whose work sits at the intersection of human-robot interaction, shared autonomy, and perception. His most cited paper introduces a novel teleoperation framework that integrates Control Barrier Functions (CBFs) with Virtual Reality, creating a safety filter that prevents human operators from issuing dangerous commands to mobile robots. This work, with 5 citations, addresses a critical challenge in teleoperation: balancing human intuition with guaranteed safety. Hebri also advances perception for autonomous navigation through his work on indoor traversability estimation. By fusing RGB camera data with Laser Range Finder (LRF) information using a dual-stream, semi-supervised attention-based architecture—leveraging Vision Transformers (ViT) and SegFormer—his approach (3 citations) enables robots to better understand complex indoor environments. Hebri’s contributions are particularly notable for their practical focus: he develops methods that bridge the gap between theoretical guarantees (like CBFs) and real-world robotic deployment. His research is directly relevant to students and researchers working on safe human-robot collaboration, teleoperation, and multi-modal perception for field robotics.
Research Focus
Key Achievements
Top Papers
- 1
- 2Indoors Traversability Estimation with RGB-Laser Fusion3 citations · 2023