Michael Lindenbaum
Papers
13
Total Citations
751
H-Index
9
About
Michael Lindenbaum is a leading figure in robotics, computer vision, and geometric learning, whose work bridges theoretical foundations and practical multi-robot systems. His seminal 1999 paper on "Distributed covering by ant-robots using evaporating traces" (274 citations) pioneered the use of chemical-like traces for decentralized robot coordination, enabling efficient exploration of unknown environments without explicit communication—a concept foundational to swarm robotics. In 2018, he co-authored "3DmFV: Three-Dimensional Point Cloud Classification in Real-Time Using Convolutional Neural Networks" (243 citations), introducing a novel approach that fuses 3D point clouds with convolutional neural networks for real-time classification, significantly advancing LiDAR-based perception in autonomous systems. His earlier work on deterministic vs. random exploration strategies (70 citations) formalized NP-hardness in robotic exploration, while his research on similarity-invariant signatures for occluded shapes and blind approximation of convex sets has influenced shape recognition and geometric inference. With over 700 total citations, Lindenbaum’s contributions to multi-robot coordination, 3D deep learning, and geometric probing continue to inspire researchers in robotics and computer vision.
Research Focus
Key Achievements
Top Papers
- 1Distributed covering by ant-robots using evaporating traces274 citations · 1999
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- 4Similarity-invariant signatures for partially occluded planar shapes55 citations · 1992
- 5Robotic Exploration, Brownian Motion and Electrical Resistance24 citations · 1998
- 6Blind Approximation of Planar Convex Shapes17 citations · 1994
- 7Localization vs. Identification of Semi-Algebraic Sets15 citations · 1998
- 8Blind approximation of planar convex sets15 citations · 1994
- 9Localization vs. identification of semi-algebraic sets13 citations · 1993
- 10