Papers
17
Total Citations
303
H-Index
9
About
Ahad Harati is a roboticist whose work has shaped how machines perceive and navigate indoor environments. His research centers on Simultaneous Localization and Mapping (SLAM), 3D perception, and mobile robotics, with a particular focus on creating lightweight, efficient algorithms for real-world deployment. Harati’s most influential contribution is the development of the Orthogonal SLAM algorithm, a fast and practical approach that exploits the right-angle geometry of indoor spaces for robust mapping and localization. This work, detailed in multiple highly-cited papers from 2007, has garnered over 60 citations and laid the groundwork for efficient embedded robotic systems. Earlier in his career, he contributed to the kinematics modeling of the University of Tehran-Pole Climbing Robot (UT-PCR), a foundational paper with over 100 citations. Harati has also advanced 3D scene understanding through techniques like GPU-accelerated plane extraction via Parallel RANSAC and wavelet-based segmentation of range scans. More recently, he has explored vision-based obstacle avoidance for drones using deep reinforcement learning, demonstrating a continued commitment to bridging perception and autonomous control. His body of work, spanning nearly two decades, reflects a consistent drive to make robots smarter, faster, and more autonomous in the spaces we inhabit.
Research Focus
Key Achievements
Top Papers
- 1Kinematics Modeling of a Wheel-Based Pole Climbing Robot (UT-PCR)104 citations · 2006
- 2FAST RANGE IMAGE SEGMENTATION FOR INDOOR 3D-SLAM34 citations · 2007
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- 6Orthogonal 3D-SLAM for indoor environments using right angle corners18 citations · 2007
- 7A new approach to segmentation of 2D range scans into linear regions13 citations · 2007
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- 9A new approach to segmentation of 2D range scans into linear regions9 citations · 2007
- 10Object classification based on a geometric grammar with a range camera7 citations · 2009