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- W2034985248 abstract "Autonomous bimodal microsystems exhibiting survivability behaviors and characteristics are able to adaptdynamically in any given environment. Equipped with a background blending exoskeleton it will have thecapability to stealthily detect and observe a self-chosen viewing area while exercising some measurable form of selfpreservationby either flying or crawling away from a potential adversary. The robotic agent in this capacityactivates a walk-fly algorithm, which uses a built in multi-sensor processing and navigation subsystem or algorithmfor visual guidance and best walk-fly path trajectory to evade capture or annihilation. The research detailed in thispaper describes the theoretical walk-fly algorithm, which broadens the scope of spatial and temporal learning,locomotion, and navigational performances based on optical flow signals necessary for flight dynamics and walkingstabilities. By observing a fly’s travel and avoidance behaviors; and, understanding the reverse bioengineeringresearch efforts of others, we were able to conceptualize an algorithm, which works in conjunction with decisionmakingfunctions, sensory processing, and sensorimotor integration. Our findings suggest that this highly complexdecentralized algorithm promotes inflight or terrain travel mobile stability which is highly suitable for nonaggressivemicro platforms supporting search and rescue (SAR), and chemical and explosive detection (CED)purposes; a necessity in turbulent, non-violent structured or unstructured environments." @default.
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- W2034985248 date "2014-03-08" @default.
- W2034985248 modified "2023-09-23" @default.
- W2034985248 title "Intelligent agents: adaptation of autonomous bimodal microsystems" @default.
- W2034985248 doi "https://doi.org/10.1117/12.2044951" @default.
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