P.-Y. Glorennec
Papers
1
Total Citations
32
H-Index
1
About
Patrick-Yves Glorennec has made pioneering contributions at the intersection of fuzzy logic, reinforcement learning, and autonomous robotics. His most-cited work, "A new mobile robot navigation method using fuzzy logic and a modified Q-learning algorithm" (2010, 32 citations), introduces a novel approach that equips mobile robots with robust obstacle avoidance and goal-seeking capabilities in unknown environments. By integrating a simple fuzzy controller with a modified Q-learning algorithm, Glorennec’s method overcomes the common problem of local minima, enabling smoother and more intelligent navigation. This work exemplifies his broader research focus on combining soft computing techniques—particularly fuzzy logic—with machine learning to create adaptive, real-time control systems. Glorennec’s contributions have been influential in advancing autonomous navigation, offering a practical and computationally efficient framework that continues to inspire researchers in robotics and intelligent control. His work stands as a key reference for those seeking to develop more flexible and resilient autonomous systems.
Research Focus
Key Achievements
Top Papers
- 1