Abstract: Methods and systems are provided for determining a source of degradation stemming from a vehicle fuel system during a refueling event. Specifically, in one example a method may include responsive to a refueling lock that enables access to a fuel tank of a fuel system being manually unlocked in order to add fuel to the fuel tank, monitoring a pressure in the fuel system and a fuel level in the fuel tank during refueling the fuel tank, and indicating degradation of the fuel system as a function of both the pressure and the fuel level. In this way, fuel system degradation may be pinpointed during a refueling event that is enabled via manual unlocking of the refueling lock.

Abstract: An electronic device may be provided with control circuitry for locating lost items. The control circuitry may determine where an item is located and may use the display or other output device to guide a user to the item. The display may display a visual guide such as an arrow, a sphere, a circle, a compass, or other visual aid that points the user in the direction of the item. The control circuitry may change the size or other characteristic of the visual aid on the display as the distance between the electronic device and the object changes. The control circuitry may change the location of the visual aid on the display as the orientation of the electronic device relative to the object changes. The display may overlay the visual aid onto live images of the user's surroundings as they are captured by a camera.

Abstract: The present teaching relates to method, system, medium, and implementation of a global model update center. At least one model is established at the model update center for detecting objects surrounding each of autonomous driving vehicles of a fleet. A plurality of labeled data items are received, from the fleet of autonomous driving vehicles, where each of the labeled data items is detected, based on the at least one model, from sensor data characterizing surroundings of the autonomous driving vehicles. The labeled data items are generated automatically on-the-fly by the autonomous driving vehicles. Based on the received labeled data items, at least some of the models are updated and model update information is accordingly generated. Such generated model update information is then distributed to the fleet of autonomous driving vehicles.

Abstract: An unmanned aerial vehicle (UAV) adapted for transit in and deployment from a projectile casing is provided. The UAV includes a wing assembly coupled to the projectile casing and the wing assembly moveable between a closed position and a deployed position. The UAV further includes a propulsion system including at least one rotor disposed on the wing assembly to generate lift, wherein in the closed position, the wing assembly is substantially integral with the projectile casing and in the deployed position, the wing assembly is extended outwards from the projectile casing.

Abstract: Motion controls for a mobile drive unit adjust linear acceleration for laden mobile drive units to decrease the likelihood of the payload tipping or bouncing off the mobile drive unit and adjust angular acceleration to reduce the risk of the drive wheels slipping while the casters align with the direction of travel.

Abstract: A method, a system, and a computer program product may be provided for updating a map database to indicate presence status of a road sign. The method may include receiving a road sign observation from at least one vehicle. The method may further include determining a road sign confidence score based on the received road sign observation, wherein the road sign observation comprises at least one of a positive road sign observation and a negative road sign observation. Additionally, the method may include updating the map database to indicate the presence status of the road sign based on the road sign confidence score being above a predetermined threshold, wherein the confidence score is based on at least one of the positive road sign observation and the negative road sign observation.

Abstract: An information collection system enables crackdown on traffic violations by vehicles to be carried out in a preferable manner. The information collection system includes an autonomous mobile object that moves autonomously based on an operation command and a server apparatus. The autonomous mobile object includes a driving information acquirer that acquires driving information relating to the state of driving of a nearby vehicle, image acquirer that captures an image of the environment of the autonomous mobile object, a detector that detects a traffic violation by a nearby vehicle based on the driving information, and a controller that sends violation information relating to a traffic violation to the server apparatus. When a traffic violation is detected by the detector, the controller sends a captured image relating to the violator's vehicle and the driving information about the violator's vehicle, to the server apparatus as the violation information.

Abstract: A method is provided for generating lane-level route guidance. Methods may include generating a first lane-level maneuver pattern between an origin and a destination based on a database of historical probe data points, each probe data point received from a probe apparatus of a plurality of probe apparatuses, where the lane-level maneuver pattern includes a recommended lane of travel along the route between the origin and the destination based on at least one of relative safety, relative popularity, or relative efficiency of the lane-level maneuver pattern; receiving a plurality of real-time or near real-time probe data points; generating an updated lane-level maneuver pattern between the origin and the destination based on the first lane-level maneuver pattern and the plurality of real-time or near real-time probe data points; and providing for route guidance of a vehicle based on the updated lane-level maneuver pattern.

Abstract: The disclosure relates to a method for operating a piloted motor vehicle, comprising the following steps carried out by a control device: determining a parking time period and a parking location of the motor vehicle on the basis of an appointment calendar signal received from a mobile terminal, which appointment calendar signal describes at least one appointment and a waiting location of the motor vehicle associated with the appointment, and creating an operating plan for the motor vehicle in accordance therewith. In accordance with at least one task signal, each of which describes a travel destination to which the motor vehicle should drive, a linking route for linking at least one travel destination to the parking location and a corresponding travel time are determined.

Abstract: Embodiments include apparatuses, methods, and systems for computer assisted or autonomous driving. An apparatus may include a storage and a safety operation controller disposed in a computer assisted or autonomous driving vehicle. The storage may store a safety operation configuration and a list of safety operations to be performed on one or more device components. The safety operation configuration and the list of safety operations may be provided by a first party. The safety operation configuration may be used to configure selected ones of the list of safety operations by a second party different from the first party to obtain configured safety operations to be performed on the one or more device components. The safety operation controller may perform the configured safety operations on the one or more device components. Other embodiments may also be described and claimed.

Abstract: A system can analyze a live sensor view of a self-driving vehicle (SDV) in accordance with a safety threshold to detect objects of interest along a route and classify each detected object of interest. When the safety threshold is not met, the system can transmit a teleassistance inquiry using LIDAR data to a backend computing system. When a certainty threshold is not met for an object of interest, the system can transmit a different teleassistance inquiry using image data to the backend computing system.

Abstract: The unified command system and/or method includes an input mechanism, a flight processor that receives input from the input mechanism and translates the input into control output, and effectors that are actuated according to the control output. The system can optionally include: one or more sensors, a vehicle navigation system which determines a vehicle state and/or flight regime based on data from the one or more sensors, and a vehicle guidance system which determines a flightpath for the aircraft.

Abstract: Methods and apparatus for preventing collisions between drones based on drone-to-drone acoustic communications are disclosed. A control system of a first drone includes a route manager to command the first drone to track a first route. The control system further includes a plurality of acoustic sensors arranged on the first drone to detect acoustic signals. The control system further includes a collision prevention engine to determine a second route based on acoustic signals detected by the acoustic sensors, the acoustic signals being received from a second drone while the first drone is tracking the first route. The second route differs from the first route to prevent a drone-to-drone collision between the first drone and the second drone. The collision prevention engine is to cause the route manager to command the first drone to track the second route instead of the first route.

Abstract: A mobile manipulator includes a moving apparatus, a manipulator that is connected to the moving apparatus, a controller configured to control the moving apparatus and the manipulator, and an environment acquisition sensor configured to acquire predetermined environmental data originating from an environment at the movement destination to which the mobile manipulator is moved by the moving apparatus in association with a position at the movement destination, and the controller controls at least one of the moving apparatus and the manipulator based on the environmental data.

Abstract: An apparatus for fault diagnosis and back-up of advanced driver assistance system sensors based on deep learning, the apparatus including: an individual sensor diagnosis unit configured to quantitatively evaluate a reliability of an output result of each sensor at each moment on the basis of a model for an output of each sensor under a normal operation; an inter-sensor mutual diagnosis unit configured to extract shared representation between the sensors and quantitatively evaluate a normal-operation reliability of the output result of each sensor on the basis of the extracted shared representation; and an integrated diagnosis unit configured to quantitatively evaluate a final reliability of each sensor on the basis of output results of the individual sensor diagnosis unit and the inter-sensor mutual diagnosis unit.

Abstract: An autonomous industrial truck, in particular an order-picking industrial truck, including an undercarriage to support the industrial truck on a roadway. The undercarriage is located on an undercarriage chassis and the industrial truck has a supporting chassis that is provided with supporting means. The supporting chassis can be adjusted relative to the undercarriage chassis between a raised position in which the supporting means are raised from the roadway and a lowered position in which the supporting means are lowered onto the roadway.

Abstract: Systems and methods are provided that employ spatial and temporal attention-based deep reinforcement learning of hierarchical lane-change policies for controlling an autonomous vehicle. An actor-critic network architecture includes an actor network that process image data received from an environment to learn the lane-change policies as a set of hierarchical actions, and a critic network that evaluates the lane-change policies to calculate loss and gradients to predict an action-value function (Q) that is used to drive learning and update parameters of the lane-change policies. The actor-critic network architecture implements a spatial attention module to select relevant regions in the image data that are of importance, and a temporal attention module to learn temporal attention weights to be applied to past frames of image data to indicate relative importance in deciding which lane-change policy to select.

Abstract: Disclosed is a driving assistance apparatus for a vehicle, including: a communication apparatus configured to perform V2X communication with an external device outside of the vehicle; and a processor which is configured to: acquire information about a set path for the vehicle; receive V2V data from one or more other vehicles through the communication apparatus; based on the information about the set path and the one or more V2V data, select, from among the one or more V2V data, data of interest which is V2V data transmitted by a vehicle of interest which is a other vehicle located on the set path; and set a recommended path for the vehicle based on the data of interest.

Abstract: A method is provided for comparing relevant information between observations. Methods may include: receiving first sensor data from a first sensor type; receiving second sensor data from a second sensor of a second sensor type, different from the first sensor type, where the first and second sensor data includes data associated with an environment of the sensors; generating a first binary bitmask of the first sensor data; generating a second binary bitmask of the second sensor data; applying a mutual information score function using the first binary bitmask and the second binary bitmask as inputs; generating a mutual information score from the mutual information score function, wherein the mutual information score represents a degree of similarity between the sensor data; and establishing a reliability of the at least one of the first sensor or the second sensor.

Abstract: Methods, apparatuses and systems for use of a magnetometer calibration (MAG-CAL) application to calibrate a magnetometer while an aircraft is in-flight including: generating a MAG-CAL calculated pattern based on a set of aircraft parameters for the in-air magnetometer calibration, the set of aircraft parameters at least comprise: speed, bank angle, altitude and position of the aircraft; generating a set of waypoints that define a calibration flight path corresponding to the MAG-CAL calculated pattern; Configuring the calibration flight path of the MAG-CAL calculated pattern to be part of the original flight path of the in-flight aircraft to enable the aircraft while flying the original flight to proceed in part on the calibration flight path corresponding to the MAG-CAL calculated pattern; and enabling the aircraft to deviate while in-flight from the original flight path to the calibration flight path to enable a sufficient level of calibration for accurate magnetometer operation.