Papers
17
Total Citations
536
H-Index
12
About
Nadine Le Fort-Piat is a leading figure in multi-agent systems, reinforcement learning, and robotic microassembly, with a career defined by pioneering contributions at the intersection of intelligent control and precision robotics. Her most influential work, the 2007 paper on *Hysteretic Q-learning*, introduced a groundbreaking algorithm for decentralized reinforcement learning in cooperative multi-agent teams, enabling independent robots to coordinate effectively without direct communication—a concept that has garnered 197 citations and remains foundational in the field. She has also made significant strides in microassembly, developing CAD model-based tracking and 3D visual servoing for constructing micro-electro-mechanical systems (MEMS), as evidenced by her 2010 paper with 89 citations. Her research extends to safe task planning for mobile robots, integrating uncertainty and local map federation, and innovative designs like a 4-DoF spherical parallel wrist for minimally invasive surgery. With over 470 citations across her top papers, Le Fort-Piat’s work bridges theoretical algorithms and practical robotic systems, advancing autonomous coordination and micro-scale manipulation. Her achievements highlight a relentless pursuit of robust, scalable solutions for complex robotic challenges, inspiring both students and researchers in robotics and artificial intelligence.
Research Focus
Key Achievements
Top Papers
- 1
- 2CAD Model-based Tracking and 3D Visual-based Control for MEMS Microassembly89 citations · 2010
- 3Safe Task Planning Integrating Uncertainties and Local Maps Federations46 citations · 2000
- 4
- 5
- 6Real-time vision-based microassembly of 3D MEMS17 citations · 2009
- 7Planning robust displacement missions by means of robot-tasks and local maps17 citations · 1997
- 8
- 9Improving Reinforcement Learning Speed for Robot Control14 citations · 2006
- 10