Abstract: In embodiments, sensors from an environment in which a mobile device is moving may be used to provide extra input to allow for improved risk analysis and detection in the environment. To prevent unwanted surveillance, proximity to the environment's sensors may be required. It will be appreciated a coordinator in the environment may assist with handling multiple sensor data provided to the mobile device, and may also assist with identifying risk. The environment may also act as a data feed allowing the mobile device to simply receive additional sensor data and perform its analysis and operation.

Abstract: Herein provided are methods and systems for producing reverse thrust in a multi-engine propeller aircraft, comprising: obtaining, at a first engine controller of a first engine of the aircraft, a first power request for the first engine for producing reverse thrust; determining, at the first engine controller, a first blade angle for a first propeller coupled to the first engine; obtaining, at the first engine controller and from a second engine controller of a second engine of the aircraft, a second power request for the second engine and a second blade angle for a second propeller coupled to the second engine; and when the second power request is indicative of a request for producing reverse thrust and when the first and second blade angles are beyond a predetermined threshold, commanding, via the first engine controller, the first engine to produce reverse thrust based on the first power request.

Abstract: Disclosed are a short cut-in target identification apparatus and an identification method thereof. The short cut-in target identification apparatus includes an occupancy distance map (ODM) information calculator configured to calculate ODM information based on subject vehicle and surrounding object information, a track information calculator configured to calculate track information based on the subject vehicle and surrounding object information, and a short cut-in target selector configured to select a short cut-in target based on the ODM information and the track information.

Abstract: Embodiments of the present application provide a charging and discharging device. The charging and discharging device includes an AC/DC converter, a first DC/DC converter, a second DC/DC converter and a control unit. The control unit is used to: receive a first charging request, the first charging request including a first charging voltage and a first charging current; set output power of the first DC/DC converter based on the first charging voltage and the first charging current; turn on the second DC/DC converter if an SOC of the energy storage unit is greater than a first threshold to charge the battery by the energy storage unit; and adjust output power of the second DC/DC converter, so as to enable a voltage difference between a bus voltage and a bus balance voltage of the charging and discharging device to be less than or equal to a preset value.

Abstract: A smart lawnmower and system and method for use of the same are disclosed. In one embodiment of the smart lawnmower, in a real world-to-simulated world (“real-to-sim”) training phase, the smart lawnmower constructs a simulated environment corresponding to a mowing-relevant portion of a real-world environment relative to semantic information, which may include received location signalization at an antenna In a simulated world-to-real world (“sim-to-real”) mowing phase, a mowing policy is applied to control the cutting subsystem and the drive subsystem in response to the semantic information, which may include the location signalization. In each of the real-to-sim training phase and the sim-to-real mowing phase, the smart lawnmower may provide a user interface including the simulated environment. Further, in the sim-to-real mowing phase, the smart lawnmower may synchronize the real world and the simulated world.

Abstract: Methods, systems, and computer readable mediums for determining a scene representation for a vehicle are provided. A disclosed method includes acquiring data from one or more sensors of the vehicle. The method further includes detecting, using processing circuitry, one or more objects in a surrounding of the vehicle based on the acquired data; determining whether an object of the detected one or more objects intersects with a vehicle lane of travel; determining whether the object is in a lane of travel of the vehicle; determining inter-vehicle gaps and cut-ins between the object and the vehicle; and rendering a scene representation including the inter-vehicle gaps and cut-ins between the object and the vehicle.

Abstract: A materials handling vehicle includes a camera, odometry module, processor, and drive mechanism. The camera captures images of an identifier for a racking system aisle and a rack leg portion in the aisle. The processor uses the identifier to generate information indicative of an initial rack leg position and rack leg spacing in the aisle, generate an initial vehicle position using the initial rack leg position, generate a vehicle odometry-based position using odometry data and the initial vehicle position, detect a subsequent rack leg using a captured image, correlate the detected subsequent rack leg with an expected vehicle position using rack leg spacing, generate an odometry error signal based on a difference between the positions, and update the vehicle odometry-based position using the odometry error signal and/or generated mast sway compensation to use for end of aisle protection and/or in/out of aisle localization.

Abstract: In various examples, a deep learning solution for path detection is implemented to generate a more abstract definition of a drivable path without reliance on explicit lane-markings—by using a detection-based approach. Using approaches of the present disclosure, the identification of drivable paths may be possible in environments where conventional approaches are unreliable, or fail—such as where lane markings do not exist or are occluded. The deep learning solution may generate outputs that represent geometries for one or more drivable paths in an environment and confidence values corresponding to path types or classes that the geometries correspond. These outputs may be directly useable by an autonomous vehicle—such as an autonomous driving software stack—with minimal post-processing.

Abstract: An apparatus including a capture device and a processor. The capture device may be configured to generate a plurality of video frames corresponding to users of a vehicle. The processor may be configured to perform operations to detect objects in the video frames, detect users of the vehicle based on the objects detected in the video frames, determine a limitation profile for the users, monitor for conditions provided by the limitation profile and generate a reaction if one or more of the conditions are met. The limitation profile may be determined in response to characteristics of the users. The characteristics of the users may be determined by performing the operations on each of the users.

Abstract: The disclosure relates to a sensor module, in particular for a safety system of a motor vehicle, having a carrier substrate, having a plurality of functional units that are arranged on or at the carrier substrate and are electrically connected to one another, wherein at least one functional unit is a sensor, having at least one analog-to-digital converter, having a communication device and optionally having a linearizer and/or compensator. There is provision for only analog functional units to be present as functional units and for the at least one analog-to-digital converter to be connected on the output side directly to the communication device.

Abstract: Methods, non-transitory computer readable media, and insurance claim analysis devices are disclosed that provide an improved, automated delta velocity determination. With this technology, one or more images of a damaged motor vehicle and contextual data, associated with an electronic insurance claim and a motor vehicle accident involving the damaged motor vehicle, are obtained. The obtained images and one or more portions of the contextual data are compared to historical sets of images of damaged motor vehicles and corresponding additional contextual data and actual delta velocity values. A delta velocity value is calculated based on the comparison. The calculated delta velocity value is provided to verify damage severity during automated processing of the electronic insurance claim.

Abstract: The present invention provides for a cognitive system using an autonomous vehicle includes a plurality of sensors configured to obtain the weather forecast for a pollution detectable area; a cognitive input to determine the pollution detectable area having highest sensitivity of pollution; a light detecting and ranging system configured to spatially probe pollution levels distributed in the pollution detectable area; an evaluation system to evaluate the probed pollution levels in the pollution detectable area; and a recommendation system for recommending an action to be taken based on evaluation system results of the probed pollution levels in the pollution detectable area, wherein the pollution levels are detected based light emitted by the light detecting and ranging system.

Abstract: In a method of controlling construction machinery, a bucket of a working device is moved along a first excavation trajectory to perform an excavation operation on the ground of a work area. A digging force exerted on the bucket during the excavation operation is calculated. A new second excavation trajectory is generated based on the calculated digging force. The bucket is moved along the second excavation trajectory.

Abstract: A method for guidance and for assisting in following a trajectory for velocity-vector piloting of an aircraft includes a step of calculating, at all times, lateral and vertical offsets of the current position of the aircraft from a target trajectory, estimated by a flight management system, and then a joining heading and a joining gradient for the aircraft to join the trajectory depending on these offsets; and a following fourth step of displaying, in head-up or head-down form, a consistent guidance symbol centered on the calculated joining heading and the calculated joining gradient for joining the trajectory, on a piloting screen showing a velocity vector. The fourth step may display, in addition to the guidance symbol, one or more items of information anticipating the next trajectory break.

Abstract: Systems and methods for use in navigating aircraft are provided. The systems can use Geometry Redundant Almost Fixed Solutions (GRAFS) or Geometry Extra Redundant Almost Fixed Solutions (GERAFS) to compute high confidence error bounds for a heading angle estimate or pitch angle derived using signals received on at least two antennas.

Abstract: Systems and methods for navigating a host vehicle. The system may perform operations including receiving, from an image capture device, at least one image representative of an environment of the host vehicle; analyzing the at least one image to identify an object in the environment of the host vehicle; determining a location of the host vehicle; receiving map information associated with the determined location of the host vehicle, wherein the map information includes elevation information associated with the environment of the host vehicle; determining a distance from the host vehicle to the object based on at least the elevation information; and determining a navigational action for the host vehicle based on the determined distance.

Abstract: A system for initiating a command of an electric vertical take-off and landing (eVTOL) aircraft includes a flight controller configured to receive a topographical datum, identify an air position as a function of a sensor and the topographical datum, wherein identifying further comprises obtaining a sensor datum as a function of the sensor, and identifying the air position as a function of the sensor datum and the topographical datum using a similarity function, determine a command as a function of the air position, and initiate the command.

Abstract: This disclosure is directed to calibrating sensors mounted on an autonomous vehicle. A dense depth map can be generated in a two-dimensional camera space using point cloud data generated by one of the sensors. Image data from another of the sensors can be compared to the dense depth map in the two-dimensional camera space. Differences determined by the comparison can indicate alignment errors between the sensors. Calibration data associated with the errors can be determined and used to calibrate the sensors without the need for calibration infrastructure.

Abstract: A work vehicle comprising: a drive wheel unit that is provided in a vehicle body and is configured to be driven by a travel drive mechanism; a work unit that is provided in the vehicle body and is configured to perform work on a work target; a battery provided in the vehicle body; a motor that is configured to receive electric power from the battery and drive the work unit; an inclination sensor configured to detect an inclination of the vehicle body relative to a horizontal plane; and a first captured image acquisition unit configured to acquire a captured image that shows surroundings of the vehicle body when the work is being performed.

Abstract: In a tilt parking mode, “a target parking position” can be accurately determined without changing a camera tilt angle and an HMI display range, and can be notified to a driver, so that the usability can be improved. A parking support device includes an external field recognition unit such as a camera and a sonar, which recognizes an external field, an information holding unit which holds information of a parking frame line recognized by the external field recognition unit, a parking region extraction unit which extracts a parking region from information of the parking frame line, a parking position determination unit which determines a target parking position from the parking region, and a path calculation unit which calculates a parking path from a current position of an own vehicle up to the target parking position.