Salvador Canas-Moreno
Papers
4
Total Citations
36
H-Index
4
About
Salvador Canas-Moreno is a neuromorphic engineer pushing the boundaries of biologically inspired computing for robotics and sensory processing. His research centers on developing hardware implementations of spiking neural networks (SNNs) to create more efficient, brain-like control systems. A key contribution is his work on neuromorphic FPGA-based infrastructures for robotic arms, where he emulates the cerebellum’s motor control—using spike-based communication to command muscles—achieving 14 citations for this foundational approach. He has also advanced Winner-Take-All (WTA) circuits for Central Pattern Generator (CPG)-based control of spiking robotic arms (11 citations), enabling more natural, adaptive limb movements. Beyond motor control, Canas-Moreno created LIPSFUS (6 citations), a pioneering neuromorphic dataset for audio-visual sensory fusion in lip reading, precisely synchronized using Address-Event-Representation sensors. His work on autonomous rover-like robots using neuromorphic computing (5 citations) further demonstrates the practical application of SNNs in real-world navigation. By bridging computational neuroscience and hardware design, Canas-Moreno is laying the groundwork for a new generation of energy-efficient, adaptive robots that learn and move like living organisms.
Research Focus
Key Achievements
Top Papers
- 1Towards neuromorphic FPGA-based infrastructures for a robotic arm14 citations · 2023
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- 4Autonomous Driving of a Rover-Like Robot Using Neuromorphic Computing5 citations · 2021