Robert Paolini
Papers
8
Total Citations
558
H-Index
7
About
Robert Paolini is a leading researcher in robotic manipulation, with a focus on enabling robots to handle objects with the dexterity and adaptability of humans. His work centers on in-hand manipulation, particularly the concept of "extrinsic dexterity," where external forces—like gravity or contact with the environment—are harnessed to reposition objects without complex finger motions. His most influential paper, "Extrinsic Dexterity: In-Hand Manipulation with External Forces" (279 citations), redefined how robots can achieve fine manipulation by leveraging the world around them. Paolini also made foundational contributions to modeling planar sliding mechanics, developing convex polynomial force-motion models that accurately predict how objects slide under friction. These models, detailed in papers with 99 and 59 citations, provide a rigorous, data-driven framework for planning grasps and regrasps under uncertainty. His work on probabilistic planning (40 citations) and statistical post-grasp manipulation (49 citations) further advances robots' ability to adapt to noisy, real-world conditions. Paolini’s research bridges theory and practice, offering elegant mathematical tools that have become essential for roboticists tackling the challenge of in-hand dexterity.
Research Focus
Key Achievements
Top Papers
- 1Extrinsic dexterity: In-hand manipulation with external forces279 citations · 2014
- 2
- 3
- 4A data-driven statistical framework for post-grasp manipulation49 citations · 2014
- 5A Probabilistic Planning Framework for Planar Grasping Under Uncertainty40 citations · 2017
- 6
- 7Data-driven statistical modeling of a cube regrasp8 citations · 2016
- 8A Data-Driven Statistical Framework for Post-Grasp Manipulation7 citations · 2013