Papers
11
Total Citations
255
H-Index
7
About
Patrick Reignier is a pioneering researcher in mobile robotics, whose work bridges reactive control, machine learning, and human-robot interaction. His early and highly influential contributions established foundational techniques for robot navigation in unknown environments. His most cited work, "Fuzzy logic techniques for mobile robot obstacle avoidance" (1994, 99 citations), introduced robust methods for real-time, sensor-based navigation that remain a cornerstone of the field. He further advanced reactive control through incremental supervised learning (1997, 37 citations) and developed adaptive perceptual categorization using fuzzy-ART neural networks (2002, 26 citations), enabling robots to autonomously structure their sensory world. In a notable shift toward social robotics, Reignier co-developed the PEAR framework (2018, 10 citations), a tool for prototyping expressive animated robots. His later research on human-robot motion (2014–2019, ~20 citations) innovatively incorporates models of human visual attention to guide robot movement, ensuring more natural and socially-aware navigation in shared spaces. With a career spanning from low-level control to high-level social cognition, Reignier’s work has profoundly shaped how robots perceive, learn, and move alongside humans.
Research Focus
Key Achievements
Top Papers
- 1Fuzzy logic techniques for mobile robot obstacle avoidance99 citations · 1994
- 2Asynchronous control of rotation and translation for a robot vehicle45 citations · 1992
- 3Incremental supervised learning for mobile robot reactive control37 citations · 1997
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- 6Supervised incremental learning of fuzzy rules9 citations · 1995
- 7Using Human Attention to Address Human–Robot Motion8 citations · 2019
- 8Human-Robot Motion: Taking Attention into Account7 citations · 2014
- 9Human-Robot Motion: An attention-based navigation approach5 citations · 2014
- 10