Abstract: It includes an intensity pattern determination section to determine an intensity pattern indicating a distribution of a magnitude of a target quantity in at least a part of a moving path of the moving object, a subarea determination section to determine, among a plurality of subareas, one or more subareas having an intensity pattern which matches or is similar to an intensity pattern determined by the intensity pattern determination section based on map information which associates area identification information which identifies each of a plurality of subareas included in a target region having a predetermined geographic range and an intensity parameter indicating a magnitude of a target quantity premeasured in the subarea, and an output section to output, as a location of the moving object, one or more subareas determined by the subarea determination section.

Abstract: A host vehicle position estimation device includes a target recognition unit configured to recognize a relative position of the vertical position target relative to a host vehicle on the basis of a detection result of an external sensor of the host vehicle, an amount-of-position error calculation unit configured to calculate an amount of position error, an amount-of-steady error calculation unit configured to calculate an amount of steady error from a distribution of the amount of position error when it is determined that the distribution of the amount of position error satisfies a steady condition, and a host vehicle position estimation unit configured to perform estimation of a vertical position of the host vehicle using the amount of steady error when the relative position of the vertical position target relative to the host vehicle is not recognized.

Abstract: A motorized cart retriever, which may be a cart pusher or a cart puller, can apply a force to a nest of human-propelled, wheeled carts to facilitate retrieval of the carts. The cart retriever can include a transceiver configured to wirelessly receive cart status information from cart transmitters of the wheeled carts and wirelessly report event data to a control unit. The cart status information may include an identification of the cart transmitter, a location of the cart, a lock or unlock status of a cart wheel, a misuse condition, etc. The event data can include the cart status information, a number of wheeled carts being retrieved, etc. The cart wheel may include a brake. The transceiver may communicate a message to the cart wheel to keep the brake unactuated during retrieval. The control unit may analyze the event data to detect traffic patterns of the carts.

Abstract: The invention relates to a method for controlling a soil working means, based on an image processing. Such a soil working means comprises a locomotion member and a working member. The method comprises the steps of acquiring at least one digital image of the soil by means of digital image acquisition means installed on the working means; processing, by means of an electronic processing unit, the at least one digital image acquired by performing at least one convolution operation on the digital image by means of a trained neural network; obtaining, by means of the electronic processing unit, at least one synthetic soil descriptor based on such a processing; generating, by means of the electronic processing unit, at least one control signal of the locomotion member or of the working member based on the synthetic soil descriptor.

Abstract: A method for tracking a trailer coupler positioned behind a tow vehicle is provided. The method includes receiving one or more images from a camera positioned on a back portion of the tow vehicle. The method also includes determining a trailer coupler position within the one or more images. The trailer coupler position associated with the trailer coupler. Additionally, the method includes receiving vehicle sensor data from one or more vehicle sensors. The method includes determining vehicle motion data based on the received vehicle sensor data. The method also includes determining an updated coupler position based on the trailer coupler position and the vehicle motion data.

Abstract: Unmanned aerial vehicle (UAV) navigation systems include a UAV charging pad positioned at a storage facility, a plurality of fiducial markers positioned at the storage facility, and a UAV. Each fiducial marker is associated with a fiducial dataset storing a position of the fiducial marker, and each fiducial dataset is stored in a fiducial map. The UAV has a navigation system that includes a camera, a fiducial navigation sub-system, a non-fiducial navigation sub-system, and logic that when executed causes the UAV to image a first fiducial marker with the camera, to transition from a non-fiducial navigation mode to a fiducial navigation mode, to access from the fiducial map the fiducial dataset storing the position of the first fiducial marker, and to navigate based upon the fiducial dataset storing the position of the first fiducial marker, into alignment with and land on the UAV charging pad.

Abstract: Excess fuel consumption monitor and feedback systems for vehicles include sensor arrays of two primary types including those sensors deployed as part of a vehicle manufacturer established sensor suite and sensors deployed as after-market sensors. Together, these sensor suites include sensors coupled to vehicle subsystems and operating environments associated with the vehicle. Data from these sensors may be used as parametric inputs to drive algorithmic calculations which have outputs that express excess fuel consumption. Expressions of excess fuel consumption may be made instantaneously as real-time feedback to a vehicle operator/driver and/or a fleet manager as part of a summary report.

Abstract: A vehicle control system includes: a terminal including an input/output unit configured to accept an operation input by a user and to display a notification to the user and an operator monitoring unit configured to monitor the user performing the operation input; and a control device configured to perform remote parking processing to move and park a vehicle in response to the operation input by the user, wherein, in the remote parking processing, the control device is configured to obtain a direction of a sightline of the user based on information obtained by the operator monitoring unit, and prohibit a movement of the vehicle in a case where the control device determines that the sightline of the user is directed to the terminal.

Abstract: A steer-by-wire system and method for a vehicle, including and utilizing: a steering wheel system including a steering wheel, an angle sensor or mechanism coupled or applied to the steering wheel and for determining an angular magnitude of the steering wheel and provide a corresponding control signal, and an angular rate sensor or mechanism coupled or applied to the steering wheel and for determining an angular rate of the steering wheel and provide a corresponding control signal offset; and a steering actuator system including a wheel angle actuator coupled to one or more wheels of the vehicle and for receiving the collective control signal and control signal offset and turning the wheels in response. The steering wheel system further includes an angular rate filter/tuner for receiving an angular rate input from the angular rate sensor or mechanism and deriving an angular offset output corresponding to the control signal offset.

Abstract: Embodiments of the present disclosure relate to a method and apparatus for controlling equipment. The method includes: acquiring an electrical signal collected by a displacement sensor; determining a displacement of a movable rod of a hydraulic cylinder relative to a cylinder tube of the hydraulic cylinder according to the electrical signal; determining, according to the displacement, a rotating angle of a mechanical arm connected to the movable rod relative to a mechanical arm connected to the cylinder tube; and controlling equipment according to the rotating angle.

Abstract: A control device may obtain data related to at least one position of an implement of a work machine that has moved to a set position. The control device may identify one or more first noise amplitudes associated with the data and may determine, based on the one or more first noise amplitudes, a noise band related to the implement vibrating at the set position. The control device may identify one or more second noise amplitudes associated with the data and may determine, based on the noise band and the one or more second noise amplitudes, that the implement has settled at the set position. The control device may allow, based on determining that the implement has settled at the set position, the implement to move to another position.

Abstract: A system for monitoring and controlling shopping cart usage comprises a wheel assembly that attaches to a shopping cart. The wheel assembly includes a wheel, a brake that can be activated to inhibit rotation of the wheel, a controller that controls the brake, a VLF receiver, and an RF transceiver. The RF transceiver may, for example, operate in a 2.4 GHz frequency band. In some implementations, the RF transceiver may be used to detect entry of the shopping cart into a checkout area of the store, and the VLF receiver may be used to detect that the shopping cart is exiting the store. The controller may activate the brake if the shopping cart attempts to exit the store without first passing through a checkout area.

Abstract: Route profile data for a vehicle is processed by acquiring a first set of the route profile data for a predetermined route section of a route of the vehicle depending on data provided by a sensor of the vehicle or another vehicle, where the first set of the route profile data is representative of at least a first local physical road characteristic of the predetermined route section. A second set of the route profile data, which is at least partly related to the predetermined route section, is read, where the second set of the route profile data is representative of at least a second local physical road characteristic. A degree of similarity between the first set of the route profile data and the second set of the route profile data is determined. The second set of the route profile data is assigned, based on the determined degree of similarity, to at least one of conditions immediately surrounding the vehicle and a time-dependent mapping function of influences that the route has on the vehicle.

Abstract: Novel tools and techniques might provide for implementing Internet of Things (“IoT”) functionality, and, in particular embodiments, implementing added services for OBD2 connection for IoT-capable vehicles. In various embodiments, a portable device (when connected to an OBD2 DLC port of a vehicle) might monitor wireless communications between a vehicle computing system(s) and an external device(s), might monitor vehicle sensor data from vehicular sensors tracking operational conditions of the vehicle, and might monitor operator input sensor data from operator input sensors tracking input by a vehicle operator. The portable device (or a server) might analyze either the monitored wireless communications or a combination of the monitored vehicle sensor data and the monitored operator input sensor data, to determine whether vehicle operation has been compromised.

Abstract: Systems and methods for controlling a vehicle. The methods comprise: receiving, by a computing device from at least one sensor, first sensor information specifying actions taken by a person while driving the vehicle or another vehicle; performing machine learning operations to learn first driving habits of the person based on at least one of the first sensor information; determining at least one autonomous driving rule for a particular driving style setting of a plurality of driving style setting options based on the machine-learned driving habits of the person; programming the particular driving style setting using the at least one autonomous driving rule; and causing the vehicle to enforce the at least one autonomous driving rule when the particular driving style setting is selected.

Abstract: Methods and apparatus are provided for detecting and assigning objects to sensed values. An object detection arrangement includes a processor that is programmed to execute a first branch of instructions and a second branch of instructions. Each branch of instructions includes receiving a modality from at least one sensor of a group of sensors via a respective interface and determining an output value based on the modality. The object detection arrangement includes an association distance matrix. Modalities of different branches of instructions define different modalities of an object external to the object detection arrangement. The object detection arrangement cumulates the output values, and the association distance matrix associates an object to the cumulated output values to thereby detect and track the object external to the object detection arrangement.

Abstract: Provided is an estimation device capable of estimating a current position with a high degree of accuracy. A driving support system includes: a vehicle mounted device 1 that is mounted on a vehicle and performs a control concerning vehicle driving support; a LIDAR 2; a gyroscope sensor 3; and a vehicle speed sensor 4. The vehicle mounted device 1 acquires, from the LIDAR 2, a measurement value ztk indicating a positional relationship between a reference landmark Lk of an index k and the own vehicle. The vehicle mounted device 1 calculates a post estimated value x{circumflex over (?)}t by correcting a prior estimated value x?t estimated, on the basis of the measurement value ztk and a position vector mk of the reference landmark Lk included in a map DB 10, from a moving speed measured by the vehicle speed sensor 4 and an angular rate measured by the gyroscope sensor 3.

Abstract: A system and connected user mobile device interface for tracking one or more shuttle buses and providing a visual display thereof along with estimated times of arrival at the connected user's location or at the shuttle bus stop closest to the connected user. The tracking system is a learning-based model that tracks vehicle movement to estimate arrival time at pre-determined geo-fence locations based on historical behavior for similar time periods and conditions.

Abstract: An apparatus and methods provide trajectory data for a geographic area. Multiple probe data sets are received or identified from one or more mobile devices. The probe data sets include time values in a first sequence associated with location values in the first sequence. At least one of the probe data sets is modified to reverse the location values such that the modified probe data set includes time values in a first sequence associated with location values in a second sequence. A location clustering algorithm is performed on the plurality of probe data sets and the modified probe data set based on the location values.

Abstract: A plurality of autonomous mobile robots includes a first mobile robot having a first module for transmitting and receiving an Ultra-Wideband (UWB) signal, and a second mobile robot having a second module for transmitting and receiving the UWB signal. The second mobile robot follows the first mobile robot using the UWB signal.