A Plausibility-based Fault Detection Method for High-level Fusion Perception Systems
Florian Geissler,
Alex Unnervik,
Michael Paulitsch
Abstract:Trustworthy environment perception is the fundamental basis for the safe deployment of automated agents such as self-driving vehicles or intelligent robots. The problem remains that such trust is notoriously difficult to guarantee in the presence of systematic faults, e.g. non-traceable errors caused by machine learning functions. One way to tackle this issue without making rather specific assumptions about the perception process is plausibility checking. Similar to the reasoning of human intuition, the final … Show more
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