A mobile robot is configured to navigate on a sidewalk and deliver a delivery to a predetermined location. The robot has a body and an enclosed space within the body for storing the delivery during transit. At least two cameras are mounted on the robot body and are adapted to take visual images of an operating area. A processing component is adapted to extract straight lines from the visual images taken by the cameras and generate map data based at least partially on the images. A communication component is adapted to send and receive image and/or map data. A mapping system includes at least two such mobile robots, with the communication component of each robot adapted to send and receive image data and/or map data to the other robot. A method involves operating such a mobile robot in an area of interest in which deliveries are to be made.

A control apparatus is provided, including: an other-vehicle emotion acquiring unit configured to acquire an other-vehicle emotion indicating an emotion of an occupant of a second vehicle different from a first vehicle; a determination unit configured to determine whether to perform notification to an occupant of the first vehicle based on the other-vehicle emotion; and a notification control unit configured to perform control to notify the occupant of the first vehicle of notification information based on the other-vehicle emotion when the determination unit determines to perform the notification.

A method for localizing a vehicle comprises transmitting first position data related to a first position of the vehicle at a first point in time from the vehicle to a server. The server computes second position data related to the first position of the vehicle at the first point in time based on the received first position data. The server transmits the second position data from the server to the vehicle. The vehicle computes third position data related to a second position of the vehicle at a second point in time based on the received second position data. The second point in time is later than the first point in time.

An approach is provided for an asymmetric evaluation of polygon similarity. The approach, for instance, involves receiving a first polygon representing an object depicted in an image. The approach also involves generating a transformation of the image comprising image elements whose values are based on a respective distance that each image element is from a nearest image element located on a first boundary of the first polygon. The approach further involves determining a subset of the plurality of image elements of the transformation that intersect with a second boundary of a second polygon. The approach further involves calculating a polygon similarity of the second polygon with respect the first polygon based on the values of the subset of image elements normalized to a length of the second boundary of the second polygon.

The present technology relates to an autonomous mobile body, an information processing method, a program, and an information processing device, by which a user experience based on an output sound of the autonomous mobile body can be improved. The autonomous mobile body includes a recognition section that recognizes a paired device that is paired with the autonomous mobile body, and a sound control section that changes a control method for an output sound to be outputted from the autonomous mobile body, on the basis of a recognition result of the paired device, and controls the output sound in accordance with the changed control method. The present technology is applicable to a robot, for example.

The present document relates to a simulation method for an autonomous vehicle, a method for controlling the autonomous vehicle, a device, an electronic apparatus, a computer-readable storage medium, and a computer program product. The method for the simulation of the autonomous vehicle comprises acquiring current state information of the autonomous vehicle; performing the simulation based on the current state information to acquire the prediction information of the autonomous vehicle; and sending the prediction information to the autonomous vehicle.

A method includes: selecting first control parameters for a perimeter intrusion detector of a mobile automation apparatus; controlling the perimeter intrusion detector according to the first control parameters, to monitor a first perimeter surrounding the mobile automation apparatus; determining that navigational data of the mobile automation apparatus defines a maneuver satisfying perimeter modification criteria; in response to determining that a likelihood of intrusion of the first perimeter associated with the maneuver exceeds a threshold, selecting second control parameters for the perimeter intrusion detector; modifying the first perimeter to a second perimeter according to the second control parameters; and controlling the perimeter intrusion detector to monitor the second perimeter.

A system includes a computer having a processor and a memory storing instructions executable by the processor to determine a first temperature of a fluid stored by a fluid storage device and then actuate a fluid heating device to add heat energy to the fluid. The instructions include instructions to determine an amount of the heat energy added to the fluid. The instructions include instructions to determine a second temperature of the fluid stored by the fluid storage device after adding the heat energy to the fluid. The instructions include instructions to determine a quantity of the fluid stored by the fluid storage device based on the amount of the heat energy added to the fluid by the fluid heating device and a difference between the first temperature and the second temperature.

The offline map generation process may collect multiple point cloud data of the same area. A perception algorithm may operate on the point cloud data to detect static objects, which may be fixed road features that do not change among the point cloud data, allowing the perception algorithm to more accurately detect the static objects. During online operation of the ADV through the area, the ADV may trim regions-of-interest (ROI) of the area to exclude the predefined static objects. The perception algorithm may execute the sensor data of the ROI in real-time to detect objects in the ROI. The may be added back to the output of the perception algorithm to complete the perception output.

A method for modifying a queue of vehicles. In one embodiment, the method includes at least one computer processor determining respective distance values between a first vehicle and one or more adjacent vehicles within a queue of vehicles. The method further includes determining a threshold distance value that corresponds to a distance required to extract the first vehicle from within the queue of vehicles. The method further includes determining a change of position corresponding to at least one adjacent vehicle to the first vehicle within the queue of vehicles based on the determined respective distance values, wherein the determined change in position moves the at least one adjacent vehicle to a distance value from the first vehicle that exceed the threshold distance value. The method further includes transmitting respective requests to the at least one adjacent vehicle to move to the determined change of position.