Shimon Schwartz

University of Waterloo

Papers

1

Total Citations

9

H-Index

1

About

Shimon Schwartz is a researcher whose work lies at the intersection of robotics, sensing, and signal processing, with a particular focus on making robotic perception faster and more efficient. His key contributions center on developing novel approaches to laser range data acquisition, a critical component for robotic mapping and localization. Schwartz is best known for his pioneering work on "Multi-Scale Saliency-Guided Compressive Sensing Approach to Efficient Robotic Laser Range Measurements" (2012), which has garnered 9 citations. This influential paper introduced a method to dramatically reduce acquisition time by dynamically sampling only a small, strategically chosen subset of measurement locations, guided by saliency—the visual importance of different scene regions. By leveraging compressive sensing principles, Schwartz demonstrated that high-quality 3D reconstructions could be achieved from far fewer measurements than traditionally required. His work represents a significant step toward enabling faster, more responsive robotic systems, particularly beneficial for real-time applications in autonomous navigation and environmental mapping. Schwartz’s research continues to inspire advances in efficient sensing for robotics.

Research Focus

Key Achievements

1
H-Index
1
Papers
9
Total Citations
9
Avg Citations/Paper
🏆 Most Cited Paper
Multi-Scale Saliency-Guided Compressive Sensing Approach to Efficient Robotic Laser Range Measurements
9 citations · 2012
📈 Most Prolific Year: 2012 (1 Papers)
🤝 Key Collaborators: 2
🏛 Institutions: University of Waterloo

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
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