Papers
11
Total Citations
329
H-Index
9
About
Antoine Petit is a computer vision and robotics researcher whose work spans two interconnected domains: vision-based object tracking and robotic manipulation of deformable objects. He has made significant contributions to the field of 3D model-based tracking, developing robust algorithms capable of estimating camera pose relative to textureless and complex objects by combining complementary edge, keypoint, and color features — work that has garnered considerable attention, with individual papers cited up to 60 times. A defining thread in Petit's research is the application of RGB-D sensing to track elastically deforming objects in real time, a technically demanding challenge with direct relevance to robotic manipulation. His pizza chef robot project exemplifies this vision — bridging fundamental computer vision research with practical humanoid robotics applications. His vision-based navigation work for autonomous space rendezvous, validated on satellite mock-ups, demonstrates the breadth of environments in which his tracking methods apply, accumulating nearly 50 citations per study. More recently, Petit has contributed to nonprehensile dynamic manipulation through the RoDyMan project and explored calibration and force sensing for soft robots using external vision systems. Across his career, his research consistently pushes the boundary between perception and physical interaction, making him a noteworthy figure in applied robotics and computer vision.
Research Focus
Key Achievements
Top Papers
- 1Real-time tracking of 3D elastic objects with an RGB-D sensor60 citations · 2015
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- 3Vision-based space autonomous rendezvous: A case study48 citations · 2011
- 4Vision-based space autonomous rendezvous: A case study45 citations · 2011
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- 8Calibration and External Force Sensing for Soft Robots Using an RGB-D Camera18 citations · 2019
- 93D object pose detection using foreground/background segmentation12 citations · 2015
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