Motilal Agrawal
Papers
9
Total Citations
1,141
H-Index
9
About
Motilal Agrawal is a leading researcher in autonomous navigation, visual odometry, and field robotics, whose work has fundamentally advanced how robots perceive and move through unstructured outdoor environments. His most influential contribution is the development of robust, real-time visual odometry systems using stereo vision, enabling accurate motion estimation on rough terrain without relying on expensive sensors. His landmark paper, "Large-Scale Visual Odometry for Rough Terrain," has garnered over 360 citations, establishing a cornerstone for subsequent research in autonomous ground vehicles. Agrawal’s early work on integrating stereo vision with inexpensive GPS for real-time outdoor localization (259 citations) demonstrated that low-cost systems could achieve reliable navigation, a breakthrough for practical field robotics. He also made key contributions to fast color/texture segmentation for outdoor robots and to the DARPA LAGR project, where his team built a complete autonomous off-road navigation system. His "Leaving Flatland" project pushed the boundaries of 3D perception and motion planning for legged robots like RHex, addressing the challenge of moving beyond flat terrain. Through a Lie algebraic approach to pose registration, Agrawal provided a mathematically rigorous framework for consistent global trajectory estimation. His work continues to inspire researchers in autonomous navigation, mapping, and field robotics.
Research Focus
Key Achievements
Top Papers
- 1Large-Scale Visual Odometry for Rough Terrain362 citations · 2010
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- 3Outdoor Mapping and Navigation Using Stereo Vision191 citations · 2008
- 4Fast color/texture segmentation for outdoor robots81 citations · 2008
- 5Mapping, navigation, and learning for off‐road traversal71 citations · 2008
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- 9Leaving Flatland: Toward real-time 3D navigation32 citations · 2009