An information processing method for a vehicle includes capturing and storing images of an area around the vehicle, and transmitting an image to an information processing apparatus when a judgment is made that a road on which the vehicle is traveling can no longer be identified by map matching, the image being captured at a time when the judgment is made.

An environment monitoring system includes N sensors, a server and a monitoring device, where N≥3. The sensors respectively generate multiple pieces of sense data related to a monitoring area. The server determines whether at least three of the pieces of sense data are abnormal, and generates position data based on the at least three pieces of abnormal sense data when the determination is affirmative. The monitoring device includes a body that is movable in the monitoring area, an image capturing module and a control module. The control module controls the body to move to a position corresponding to the position data, and the image capturing module captures an image at said position.

Various embodiments include methods and systems for autonomous driving systems for using map data in performing an autonomous driving function. Various embodiments may include accessing map data regarding an object or feature in the vicinity of the vehicle, accessing confidence information associated with the map data, and using the confidence information in performing an autonomous or semi-autonomous driving action by the processor. The confidence information may be stored in the map database or in a separate data structure accessible by the processor. Methods of generating map safety and confidence information may include receiving information regarding a map object or feature including a measure of confidence in the information, using the received measure of confidence to generate safety and confidence information regarding the object or feature, and storing the safety and confidence information for access by vehicle autonomous and semi-autonomous driving systems.

A position estimation apparatus comprises: a satellite positioning device for calculating satellite positioning position-information based on satellite information; an autonomous positioning device for calculating autonomous positioning position-information based on vehicle information; a geographic map information storage device for storing geographic map information; a positioning-device estimation device for estimating a positioning device whose error of estimation position on a mobile object becomes minimum based on first position information and the geographic map information, and for calculating positioning-device information related to the positioning device; and a position estimation device for calculating second position information based on the satellite and autonomous positioning position-information and the positioning-device information, wherein the positioning-device estimation device estimates a positioning device to be changed over thereto, before its positioning accuracy will be reduced; and the position estimation device verifies go/no-go determination of usage on the positioning device estimated, and estimates a position of the mobile object.

A computing device configured to: obtain images representative of an environment of a host vehicle, the host vehicle traveling on a roadway; detect, from the images, a mark located on the roadway; identify, from the images, points corresponding to the mark on the roadway; identify the mark as a type of roadway marking, corresponding to the identified points, the type of roadway marking selected from multiple types of roadway markings; determine a position of the mark on the roadway relative to the host vehicle, using the identified points corresponding to the mark; and determine a trajectory to navigate the host vehicle on the roadway, based on the position of the mark within the roadway and the type of roadway marking.

In various examples, map data or geospatial data is used to identify a subset of sensor data having a higher likelihood of including representations of a target object of interest from a larger set of sensor data. Feature vectors corresponding to the subset of sensor data may then be compared to template feature vectors corresponding to the target object in order to confirm the depiction of the target object in the sensor data. The identified sensor data may be used to train one or more machine learning model to compute outputs that correspond to object identification. The trained machine learning models may be used to identify objects in order to aid an autonomous or semi-autonomous machine in a surrounding environment.

An apparatus, a method and a computer program product are provided for updating link information on a client device. The method may include determining at least one map area comprising one or more links, the map area having at least one map area identifier, Sending to a data service, a request for at least one categorized link. Receiving, from the data service, at least one bloom filter, the at least one bloom filter encoding the at least one categorized link, determining one or more link identifiers for the one or more links in the map area and associating candidate link of the one or more links to the at least one categorized link, based on the link identifier of the at least one candidate link satisfying the at least one received bloom filter, to update the link information on the client device.

A system, method, autonomous mobile robot, and computer readable media enabling location-based autonomous navigation using a virtual world system. The system comprises at least one server computing device having at least one processor and a memory. The memory stores a virtual world system and computer-readable instructions. The virtual world system comprises at least one virtual object being spatially defined by virtual three-dimensional coordinates that correspond to three-dimensional coordinates of a corresponding physical object in a physical environment. The instructions cause the at least one server computing device to provide a navigation engine configured to compute a navigation route of at least one autonomous mobile robot using at least the virtual three-dimensional coordinates of the at least one virtual object, enabling the at least one autonomous mobile robot to autonomously navigate the physical environment by reference to a virtual replica of the physical environment comprised in the virtual world system.

A system for mapping traffic lights and for determining traffic light relevancy for use in autonomous vehicle navigation. The system may include at least one processor programmed to: receive at least one location identifier associated with a traffic light; receive a state identifier associated with the traffic light; receive navigational information indicative of one or more aspects of motion of the first vehicle along the road segment, and determine, based on the navigational information, a lane of travel traversed by the first vehicle along the road segment. The processor may also determine whether the traffic light is relevant to the lane of travel traversed by the first vehicle; update an autonomous vehicle road navigation model relative to the road segment; and distribute the updated autonomous vehicle road navigation model to a plurality of autonomous vehicles.

Methods, devices, and systems for a tag for order fulfillment are described herein. One or more embodiments include a number of tags each associated with a corresponding inventory bin of a warehouse, each tag configured to broadcast unique identification information, and a mobile device configured to receive, from a database, order information including identification information of one of the number of tags and a type and a quantity of an item of an inventory bin of the warehouse corresponding to the tag, and scan for identification information of the tag.