'An autonomous vehicle is able to navigate city streets and other less-busy environments by recognizing pedestrians, other vehicles, obstacle
PublishedResearchers at Cornell University have developed a way to help autonomous vehicles create “memories” of previous experiences and use them in future navigation, especially during adverse weather conditions when the car cannot safely rely on its sensors.
, professor of computer science. “For example, a car may mistake a weirdly shaped tree for a pedestrian the first time its laser scanner perceives it from a distance, but once it is close enough, the object category will become clear. So, the second time you drive past the very same tree, even in fog or snow, you would hope that the car has now learned to recognize it correctly.”
HINDSIGHT is an approach that uses neural networks to compute descriptors of objects as the car passes them. It then compresses these descriptions, which the group has dubbed SQuaSH features, and stores them on a virtual map, like a “memory” stored in a human brain. HINDSIGHT is a precursor to additional research the team is conducting, MODEST , that would go even further, allowing the car to learn the entire perception pipeline from scratch.
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