A control apparatus of a robot cleaner includes a user interface unit to receive a user command controlling the robot cleaner; a controller to generate a control signal to receive a map of a cleaning area, based on the user command; and a communicator to receive the map of the cleaning area from an external server or the robot cleaner, based on the control signal. An embodiment may download or generate a map of a cleaning area and to allow a map editing to be performed by a user. An embodiment may set and edit a cleaning schedule. When setting the cleaning schedule, an embodiment may recommend a cleaning schedule based on cleaning history data. An embodiment may automatically determine whether the environment is changed or whether the cleaning is available, while the robot cleaner performs the cleaning, and it may be possible to actively deal with this.

A system for an autonomous vehicle that receives driving environment information corresponding to a driving environment provided by another autonomous vehicle, and determines a navigation route based on a degree of reliability of the driving environment information provided by the another autonomous vehicle.

Various applications for use of mass estimations of a vehicle, including to control operation of the vehicle, sharing the mass estimation with other vehicles and/or a Network Operations Center (NOC), organizing vehicles operating in a platoon and/or partially controlling the operation of one or more vehicles operating in a platoon based on the relative mass estimations between the platooning vehicles. When vehicles are operating in a platoon, the relative mass between a lead and a following vehicle may be used to scale torque and/or brake commands generated by the lead vehicle and sent to the following vehicle.

A switch reporting device including at least one display screen, a high resolution camera, a code reader, at least one memory and one or more processors, the switch reporting device configured to determine a position of an unmonitored switch in a railway by capturing an image of one or more portions associated with the unmonitored switch, generating switch position data based on the image of one or more portions associated with the unmonitored switch, and updating a switch position record for the unmonitored switch with the switch position data. The switch reporting device includes one or more mobile computers or an EOT device for monitoring and reporting switch position data for an unmonitored switch.

Detecting potential safety issues is provided. An image is received from an imaging device located on a vehicle. The image is analyzed to identify an object. The object identified in the image is compared with images of objects stored in a database to determine a potential safety issue associated with the object. A set of protective roadway barriers is identified in an area of the vehicle and the object. An adjustment to operation of the vehicle is calculated based on the potential safety issue and the set of protective roadway barriers. The operation of the vehicle is adjusted based on the calculated adjustment.

This disclosure describes a solution to facilitate interactions between non-autonomous and autonomous vehicles when sharing a road system. An edge network can provide resources to the vehicles such that non-autonomous and autonomous vehicles can operate in a harmonic and safe manner. Additionally, an augment reality display of the vehicles can be used to further facilitate communication between non-autonomous and autonomous vehicles. For example, a predicted direction or an imperative direction associated with an autonomous vehicle can be communicated to a non-autonomous vehicle such that an augmented reality display of the non-autonomous vehicle can alert the driver of the non-autonomous vehicle of a of such to increase safety measures.

The disclosure includes embodiments for selecting Vehicle-to-Everything (V2X) data to be shared among vehicles in a cooperative vehicular system based on an uncertainty criterion. In some embodiments, a method for an ego vehicle includes: determining, by a sensor set of the ego vehicle, ego V2X data describing ego object information about a set of objects included in a roadway environment; receiving remote V2X data provided by a remote vehicle, where the remote V2X data describes remote object information about the set of objects from a perspective of the remote vehicle; determining uncertainty data describing an uncertainty about the ego object information based at least in part on an analysis of the ego object information relative to the remote object information; and updating the ego V2X data to form updated ego V2X data that describes ego object information that satisfies the uncertainty criterion.

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for using surfels for vehicle localization. One of the methods includes obtaining surfel data comprising a plurality of surfels, wherein each surfel corresponds to a respective different location in an environment, and each surfel has associated data that comprises a stability measure, wherein the stability measure characterizes a permanence of a surface represented by the surfel; obtaining sensor data for a plurality of locations in the environment, the sensor data having been captured by one or more sensors of a first vehicle; determining a plurality of high-stability surfels from the plurality of surfels in the surfel data; and determining a location in the environment of the first vehicle using the plurality of selected high-stability surfels and the sensor data.

A storage system comprises one or more automated guided vehicles, one or more centralized supervisory systems, one or more parts container storage spaces disposed within a defined two dimensional space comprising one or more addressable parts container spaces and parts bins which comprise a part identifier and which are configured to fit at least partially within the parts container storage space. The automated guided vehicles comprise a controllable autonomous parts container base and one or more position sensors operatively in communication with a controller and operative to determine a coordinate location of the automated guided vehicle within a defined two dimensional space in real time without relying on a map stored in the controller.

Methods and systems for assessing, detecting, and responding to malfunctions involving components of autonomous vehicle and/or smart homes are described herein. Autonomous operation features and related components can be assessed using direct or indirect data regarding operation. Such assessment may be performed to determine the condition of components for salvage following a collision or other loss-event. To this end, the information regarding a plurality of components may be received. A component of the plurality of components may be identified for assessment. Assessment may including causing test signals to be sent to the identified component. In response to the test signal, one or more responses may be received. The received response may be compared to an expected response to determine whether the identified component is salvageable.