X Development LLC

Robert Boschgmbh

Google Inc.

Jonas Witt

Elmar Mair

Karsten Behrendt

Methods, systems, and apparatus for receiving a reference to an object located in an environment of a robot, accessing mapping data that indicates, for each of a plurality of object instances, respective probabilities of the object instance being located at one or more locations in the environment, wherein the respective probabilities are based at least on an amount of time that has passed since a prior observation of the object instance was made, identifying one or more particular object instances that correspond to the referenced object, determining, based at least on the mapping data, the respective probabilities of the one or more particular object instances being located at the one or more locations in the environment, selecting, based at least on the respective probabilities, a particular location in the environment where the referenced object is most likely located, and directing the robot to navigate to the particular location.

Semantic mapping of environments for autonomous devices

Methods, systems, and apparatus for receiving a mapping of a property that includes a three-dimensional representation of the property, receiving observations of the property that each depict a portion of the property, providing the mapping and the observations to an object mapping engine, receiving an object mapping of the property, wherein the object mapping includes a plurality of object labels that each identify an object that was recognized from the observations and a location of the object within the three-dimensional representation that corresponds to a physical location of the object in the property, and obtaining a semantic mapping of the property that identifies semantic zones of the property with respect to the three-dimensional representation, wherein the semantic mapping is generated based on an output that results from a semantic mapping model processing the object mapping.

Semantic zone separation for map generation

Methods, systems, and apparatus for receiving data that represents a portion of a property that was obtained by a robot, identifying, based at least on the data, objects that the data indicates as being located within the portion of the property, determining, based on the objects, a semantic zone type corresponding to the portion of the property, accessing a mapping hierarchy for the property, wherein the mapping hierarchy for the property specifies semantic zones of the property that have corresponding semantic zone types and are associated with locations at the property, and specifies characteristics of the semantic zones, and selecting, from among the semantic zones and based at least on the semantic zone type and the data, a particular semantic zone, and setting, as a current location of the robot at the property, a particular location at the property associated with the particular semantic zone.

Semantic place recognition and localization

A method and system for navigating a vehicle using automatically labeled images. The system includes a camera configured to capture an image of a roadway and an electronic processor communicatively connected to the camera. The electronic processor is configured to load a map that includes a first plurality of features and receive the image. The image includes a second plurality of features. The electronic processor is further configured to project the map onto the image; detect the second plurality of features within the image; and align the map with the image by aligning the first plurality of features with the second plurality of features. The electronic processor is further configured to copy a label describing one of the first plurality of features onto a corresponding one of the second plurality of features to create a labelled image and to use the labelled image to assist in navigation of the vehicle.

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Palo Alto, CA, United States of America

Jonas Witt