Susanna Ricco

Duke University, Harvey Mudd College

Papers

2

Total Citations

13

H-Index

2

About

Susanna Ricco is a researcher whose work bridges computer vision, robotics, and autonomous navigation, with a particular focus on enabling machines to perceive and move through the world using minimal, cost-effective hardware. Her key research areas include monocular localization, occupancy grid mapping, and resource-efficient robotics. Ricco’s most notable contribution is her pioneering work on "textured occupancy grids," a versatile data structure that allows for camera-based localization without relying on traditional landmarks or features. This approach, detailed in her 2011 paper, has garnered 11 citations and offers a compelling alternative to feature-dependent methods, enabling robots to render human-readable views and perform laser rangefinder-style localization using only a single camera. Earlier in her career, Ricco explored the concept of "scavenging" with a laptop robot (2005), demonstrating how commodity laptops, web cameras, and inexpensive sensors could replace engineered precision with computational power—a prescient idea that anticipates today’s low-cost robotics platforms. Her work challenges conventional assumptions about sensor complexity, advocating for smarter algorithms over expensive hardware. With a clear focus on practical, accessible solutions, Ricco’s research continues to inspire students and researchers interested in efficient, vision-based navigation and the democratization of robotic technology.

Research Focus

Key Achievements

2
H-Index
2
Papers
13
Total Citations
7
Avg Citations/Paper
🏆 Most Cited Paper
Textured occupancy grids for monocular localization without features
11 citations · 2011
📈 Most Prolific Year: 2011 (1 Papers)
🤝 Key Collaborators: 6
🏛 Institutions: Duke University, Harvey Mudd College

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago