Roberto Martin-Martin

Stanford University

Papers

2

Total Citations

116

H-Index

2

About

Roberto Martin-Martin is a leading roboticist whose research lies at the intersection of computer vision, manipulation, and autonomous navigation in unstructured environments. His foundational work on **Mechanical Search** (2019, 108 citations) addresses a critical real-world challenge: enabling robots to locate and retrieve a target object buried under clutter in bins or shelves—a task essential for warehouses, homes, and retail automation. This work established a new problem class and practical algorithms for interactive, multi-step object retrieval. More recently, Martin-Martin has advanced **visual navigation** by developing probabilistic models that allow mobile robots to robustly follow a visual trajectory defined by a sequence of images, even amid environmental changes or obstacles. His 2021 paper on bidirectional image prediction demonstrates how a robot with only a single RGB fisheye camera can achieve human-like path following. By bridging perception and action, Martin-Martin’s contributions are shaping the next generation of robots that can operate safely and efficiently in the messy, dynamic spaces where people live and work.

Research Focus

Key Achievements

2
H-Index
2
Papers
116
Total Citations
58
Avg Citations/Paper
🏆 Most Cited Paper
Mechanical Search: Multi-Step Retrieval of a Target Object Occluded by Clutter
108 citations · 2019
📈 Most Prolific Year: 2019 (1 Papers)
🤝 Key Collaborators: 13
🏛 Institutions: Stanford University

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago