Chloe Gourrat
Papers
1
Total Citations
4
H-Index
1
About
Chloe Gourrat is a roboticist whose research lies at the intersection of tactile sensing, manipulation, and autonomous decision-making. Her work focuses on enabling robots to learn from failure—specifically, by leveraging tactile events during grasp failures to infer critical object properties like surface texture and weight. In her highly cited 2019 paper, *Determining Object Properties from Tactile Events During Grasp Failure*, she demonstrated how robots can extract meaningful data from unsuccessful grasps, transforming errors into opportunities for more robust regrasp strategies. This approach challenges traditional robotic paradigms that treat failure as purely negative, instead framing it as a rich source of sensory information. Though early in her career, Gourrat’s contributions have already garnered attention for their practical implications in industrial automation and assistive robotics, where adaptive manipulation is essential. Her work underscores a shift toward resilient, learning-driven robotic systems that improve through experience. With a growing citation record and a focus on bridging perception and action, Gourrat is establishing herself as a promising voice in the field of dexterous manipulation and tactile intelligence.
Research Focus
Key Achievements
Top Papers
- 1Determining Object Properties from Tactile Events During Grasp Failure4 citations · 2019