Peter Henry
Papers
7
Total Citations
3,226
H-Index
7
About
Peter Henry is a pioneering researcher in robotics and computer vision, best known for his groundbreaking work in 3D mapping, autonomous navigation, and RGB-D perception. His seminal paper "RGB-D mapping: Using Kinect-style depth cameras for dense 3D modeling of indoor environments" (2012, 1,170 citations) revolutionized indoor robotics by demonstrating how low-cost depth cameras could generate dense, accurate 3D models for robot navigation and manipulation. Henry further advanced autonomous flight with "Visual Odometry and Mapping for Autonomous Flight Using an RGB-D Camera" (2016, 610 citations), enabling drones to navigate GPS-denied environments using visual and depth data. His research also tackles socially-aware robotics: in "Learning to navigate through crowded environments" (2010, 228 citations), he developed planners that mimic human motion behavior, allowing robots to move safely through busy spaces like malls and sidewalks. Henry’s contributions extend to object manipulation and discovery, with work on in-hand 3D modeling and scene comparison for object recognition. With over 3,000 total citations, his innovations have shaped modern robotics, making autonomous systems more capable in real-world, unstructured environments.
Research Focus
Key Achievements
Top Papers
- 1
- 2RGB-D Mapping: Using Depth Cameras for Dense 3D Modeling of Indoor Environments811 citations · 2013
- 3Visual Odometry and Mapping for Autonomous Flight Using an RGB-D Camera610 citations · 2016
- 4Learning to navigate through crowded environments228 citations · 2010
- 5Manipulator and object tracking for in-hand 3D object modeling168 citations · 2011
- 6
- 7Toward object discovery and modeling via 3-D scene comparison75 citations · 2011