Margarita Grinvald
Papers
4
Total Citations
43
H-Index
3
About
Margarita Grinvald is a leading researcher in robotics and computer vision, whose work is central to enabling autonomous systems to perceive, track, and interact with dynamic, unstructured environments. Her primary research areas include multi-object tracking and reconstruction, 3D scene understanding, and mobile manipulation. Grinvald’s most impactful contribution is the TSDF++ formulation, which provides a groundbreaking method for simultaneously tracking and reconstructing multiple moving objects in a scene—a critical capability for autonomous navigation and human-robot interaction. This work has garnered 24 citations, reflecting its significance in the field. She also developed the "Go Fetch" framework for mobile manipulation in unstructured settings, addressing key challenges in service robotics. Additionally, her "Modelify" approach enables robots to incrementally build 3D object models for map completion, and she contributed the CLUBS dataset, a valuable resource for training and evaluating object detection and segmentation algorithms in cluttered scenes. Through these achievements, Grinvald is advancing the frontier of robots that can operate safely and intelligently in the real world.
Research Focus
Key Achievements
Top Papers
- 1
- 2Go Fetch: Mobile Manipulation in Unstructured Environments12 citations · 2020
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