Hanno Gerd Meyer
Papers
5
Total Citations
52
H-Index
5
About
Hanno Gerd Meyer is a robotics researcher whose work bridges bio-inspired vision, embedded systems, and human-robot interaction. His primary research areas include neuromorphic visual processing for collision avoidance, resource-efficient embedded computing architectures, and biosignal-based control for wearable robotic systems. Meyer’s major contributions lie in developing computationally frugal, biologically plausible models for robot navigation. Notably, his 2020 paper on resource-efficient bio-inspired visual processing for the hexapod walking robot HECTOR (15 citations) demonstrates how insect-brain-inspired algorithms can be implemented on integrated System-on-Chip modules, enabling real-time collision avoidance with minimal power consumption. In parallel, his 2023 work on sEMG-based prediction of forearm movements (14 citations) advances intuitive control of assistive devices by incorporating individual anatomical and physiological measures into biomechanical models, reducing optimization complexity. Meyer also contributed to reconfigurable FPGA-SoC-based computer modules for embedded vision (6 citations), showcasing his expertise in hardware-software co-design. His research has direct applications in rehabilitation robotics, prosthetics, and autonomous mobile robots, making him a notable figure in the intersection of bio-inspired computing and practical robotic systems.
Research Focus
Key Achievements
Top Papers
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