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A stereo visual-servoing framework for an autonomous underwater vehicle (AUV) that derives a stable 3D relative state from stereo images through target-specific depth extraction and Kalman filtering and employs adaptive model-fusion predictive control.
FineMote reduces perception-to-decision latency in robotic systems by statically orchestrating control firmware for tree-structured device models, achieving better timing behavior with minimal overhead.