Papers
3
Total Citations
61
H-Index
3
About
Bruno Sauvet is a robotics researcher whose work bridges the gap between autonomous manipulation and nanoscale characterization. His primary research areas include robotic grasping, model-based manipulation of unknown objects, and nanorobotics for materials science. Sauvet’s most significant contribution is a model-based scooping grasp strategy that enables two-fingered grippers to autonomously pick unknown objects from cluttered environments—a fundamental challenge in industrial and service robotics. This work, published in 2018, has garnered 45 citations, reflecting its practical value. He further advanced the field by addressing the complexities of grasping unknown objects from random piles, where occlusion and proximity limit feasible grasps, proposing a simple yet effective approach that has earned 10 citations. In a different vein, Sauvet has also contributed to nanorobotics, developing a versatile in-situ method for electrically characterizing carbon nanotubes (CNTs) within a scanning electron microscope. By using 6-degree-of-freedom nanopositioning robots, his approach allows for precise, adaptable measurements of CNT properties, a technique that has received 6 citations. This dual expertise—from macro-scale grasping to nano-scale manipulation—demonstrates Sauvet’s versatility and his impact on both autonomous robotics and advanced materials research.
Research Focus
Key Achievements
Top Papers
- 1
- 2Model-Based Grasping of Unknown Objects from a Random Pile10 citations · 2019
- 3