Adam Perrett
Papers
1
Total Citations
14
H-Index
1
About
Adam Perrett is a researcher at the forefront of neuromorphic engineering and bio-inspired robotics, with a focus on developing energy-efficient, event-driven systems for embodied intelligence. His major contributions center on implementing biologically plausible attention mechanisms on SpiNNaker—a massively parallel, neuromorphic hardware platform—to enable real-time, low-power visual processing in humanoid robots. Perrett’s most cited work, “Event driven bio-inspired attentive system for the iCub humanoid robot on SpiNNaker” (2022, 14 citations), demonstrates how a robot can leverage perceptual feature organization to guide its gaze and selectively analyze salient regions of a scene, mimicking the human visual attention system. This approach allows robots to better understand complex environments without the computational overhead of traditional frame-based processing. By bridging neuroscience principles with practical robotics, Perrett’s research contributes to the development of more autonomous, responsive, and energy-aware machines. His work is particularly notable for its integration of event-driven sensors and spiking neural networks, offering a scalable pathway toward truly brain-inspired robotic perception.
Research Focus
Key Achievements
Top Papers
- 1