Papers
7
Total Citations
110
H-Index
6
About
Bernard Girau is a leading figure in bio-inspired robotics and neuromorphic engineering, whose work bridges the gap between biological neural mechanisms and embedded hardware systems. His primary research focuses on Central Pattern Generators (CPGs)—neural circuits that produce rhythmic outputs for locomotion—and their efficient implementation in robots. Girau’s major contributions include developing perception-driven adaptive CPG control for hexapod robots (31 citations), which enables dynamic, real-time gait adjustments based on environmental feedback. He also pioneered hardware/software codesign for neural networks (18 citations) and FPGA-based embedded CPG systems (22 and 8 citations), demonstrating how configurable hardware can achieve low-latency, scalable locomotion control for quadruped and hexapod robots. His work on connectionist approaches to visual perception of motion (11 citations) further extends his impact into perception-action loops. Girau’s notable achievements include advancing block-synchronous harmonic control for scalable trajectory planning, a method that integrates harmonic potential fields with FPGA architectures for efficient navigation. With over 100 combined citations, his research has significantly influenced the development of autonomous, energy-efficient legged robots, making him a key reference for students and researchers in neuromorphic robotics and embedded intelligence.
Research Focus
Key Achievements
Top Papers
- 1Perception-driven adaptive CPG-based locomotion for hexapod robots31 citations · 2015
- 2
- 3Hardware/Software Codesign for Embedded Implementation of Neural Networks18 citations · 2007
- 4Configurable Embedded CPG-Based Control for Robot Locomotion17 citations · 2012
- 5A CONNECTIONIST APPROACH FOR VISUAL PERCEPTION OF MOTION11 citations · 2004
- 6
- 7Block-synchronous Harmonic Control for Scalable Trajectory Planning3 citations · 2008