Abstract: A navigation system may receive a captured image acquired by a camera onboard a host vehicle; determine a localized position of the host vehicle relative to a map representative of the road segment; generate based on the localized position of the host vehicle and three-dimensional location information associated with the plurality of topography features, a two-dimensional image representation of a plurality of road topography features; analyze the captured image and the two-dimensional image representation and determine three-dimensional information for at least one object represented in the captured image, but not represented in the map representative of the road segment, based on the three-dimensional location information associated with the plurality of topography features included in the map; determine, based on the three-dimensional information for the at least one object, at least one navigational action for the host vehicle; and cause the host vehicle to implement the at least one navigational action.

Abstract: A system for generating map information for use in navigating a host vehicle may comprise at least one processor programmed to: receive drive information from each of a plurality of vehicles that traversed the road segment, wherein the drive information includes one or more indicators of a road topography feature and the drive information includes actual trajectory information; generate, based on the one or more indicators of the actual trajectory information, a map including at least a portion of a drivable path for the road segment; provide the map as input to at least one trained model configured to generate, in response to the provided input, an output including an updated map with at least one updated drivable path for the road segment; and provide the updated map to at least one host vehicle navigation system.

Abstract: A system for recovering physical properties from a non-linear medium includes a wave field modeler, a properties adjuster and a medium properties recoverer. The wave field modeler models a wave field generated by a transmitted pulse traveling in the non-linear medium and generates a predicted transducer output from the modeled wave field. The wave field modeler is a neural network having a neural network representation of a non-linear wave function of the physical properties of the wave field. The properties adjuster optimizes a loss function between the predicted transducer output and a measured transducer output and generates an improved set of the physical properties. The properties adjuster operates a backpropagator using the neural network representation and activates the wave field modeler with the improved set of the physical properties. The medium properties recoverer outputs a current improved set of the physical properties once the properties adjuster finishes operation.