Resource-efficient bio-inspired visual processing on the hexapod walking robot HECTOR

Hanno Gerd Meyer, Daniel Klimeck, Jan Paskarbeit, Ulrich Rückert, Martin Egelhaaf, Mario Porrmann, Axel Schneider, Olena Riabinina
<span title="2020-04-01">2020</span> <i title="Public Library of Science (PLoS)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/s3gm7274mfe6fcs7e3jterqlri" style="color: black;">PLoS ONE</a> </i> &nbsp;
Emulating the highly resource-efficient processing of visual motion information in the brain of flying insects, a bio-inspired controller for collision avoidance and navigation was implemented on a novel, integrated System-on-Chip-based hardware module. The hardware module is used to control visually-guided navigation behavior of the stick insect-like hexapod robot HECTOR. By leveraging highly parallelized bio-inspired algorithms to extract nearness information from visual motion in dynamically
more &raquo; ... reconfigurable logic, HECTOR is able to navigate to predefined goal positions without colliding with obstacles. The system drastically outperforms CPU- and graphics card-based implementations in terms of speed and resource efficiency, making it suitable to be also placed on fast moving robots, such as flying drones.
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1371/journal.pone.0230620">doi:10.1371/journal.pone.0230620</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/32236111">pmid:32236111</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/wclrd2h2r5hdhkiwew2xck7maq">fatcat:wclrd2h2r5hdhkiwew2xck7maq</a> </span>
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