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vcharge SemanticMap2014LD

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Published on Oct 3, 2014

taken into account in the vehicle’s current motion plan and speed. Also labeling of parking spots, could be
crucial in other V-Charge tasks as efficient assignment of parking spaces and local planning. Because many
of these useful semantic cues are fixed in place, it makes sense to build up reusable semantic maps of the
areas in which we want our autonomous cars to operate. Usually these maps are created manually but offers
guarantees that are currently not available when using unsupervised machine learning classifiers. We describe the pipeline of UOXF.DF to create semantic maps automatically using active learning for road mark (e.g parking spot) classification.

Collaborators:
Oxford University
Hugo Grimmett, Lina Paz, Pedro Pinies, Chi Tong
Ingmar Posner, Paul Newman

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