Abstract: An information processing apparatus capable of communicating with a vehicle includes a control unit and a communication unit. The control unit is configured to acquire, from the vehicle via the communication unit, vehicle information including at least one of open-close information of a door of the vehicle and location information of the vehicle, and determine a personality of a driver of the vehicle based on the vehicle information.

Abstract: Systems and methods are provided for navigating a host vehicle. In an embodiment, a processing device may be configured to receive at least one image captured by an image capture device, the at least one image being representative of an enviromnent of the host vehicle; analyze the at least one image to identify an object in the environment of the host vehicle; determine a location of the host vehicle; receive map information associated with the determined location of the host vehicle, wherein the map information includes lane width information associated with a road in the environment of the host vehicle; determine a distance from the host vehicle to the object based on at least the lane width information; and determine a navigational action for the host vehicle based on the determined distance.

Abstract: A first process acquires a true value of the position of a predetermined portion. A second process acquires a reference position of a work machine. A third process determines a plurality of correction candidate values of a parameter. The correction candidate values are used so that a calculation value of the position of the predetermined portion calculated based on the parameter from the reference position matches the true value. A fourth process calculates an assessment value indicative of the difference between the true value and a calculation value for each of plurality of correction candidate values. A fifth process determines a confirmation correction value of the parameter from among the plurality of correction candidate values based on the assessment value.

Abstract: A system for monitoring shopping baskets (e.g., baskets on human-propelled carts, motorized carts, or hand-carried baskets) can include a computer vision unit that can image a surveillance region (e.g., an exit to a store), determine whether a basket is empty or loaded with merchandise, and assess a potential for theft of the merchandise. The computer vision unit can include a camera and an image processor programmed to execute a computer vision algorithm to identify shopping baskets and determine a load status of the basket. The computer vision algorithm can comprise a neural network. The system can identify an at least partially loaded shopping basket that is exiting the store, without indicia of having paid for the merchandise, and execute an anti-theft action, e.g., actuating an alarm, notifying store personnel, activating a store surveillance system, activating an anti-theft device associated with the basket (e.g., a locking shopping cart wheel), etc.

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 of the fiducial markers is associated with a fiducial dataset storing a position of the corresponding fiducial marker, and the fiducial datasets are stored in a fiducial map. The UAV includes a camera and logic that when executed causes the UAV to image a first fiducial marker, to access from the fiducial map a first fiducial dataset storing the position of the first fiducial marker, and to navigate based upon the first fiducial dataset.

Abstract: Provided is a medium storing instructions that when executed by a processor of a first wheeled device effectuates operations including: capturing sensor readings of an environment; finding a position of the first wheeled device within a map of the environment based on at least some of the sensor readings; and generating a new map of the environment when the processor is unable to load the previously generated map or cannot find the position of the first wheeled device within the previously generated map; wherein: the map is previously generated with the processor of the first wheeled device or a processor of a second wheeled device; the map is loaded into a memory of the first wheeled device at a beginning of each work session; and the processor of the first wheeled device iteratively tracks the position of the first wheeled device while performing a task.

Abstract: The present disclosure relates to an agriculture operation monitoring system comprises at least one implement adapted to be mounted to a work vehicle, a wireless communication element, and a data storage and processing system. The implement comprises one or a plurality of sensors arranged to obtain sensor signals related to at least one hydraulic function of the implement and a local control element. The local control element is arranged to receive sensor signals obtained by the at least one sensor, to determine at least one present setting related to an operational status of the implement based on the received sensor signals and to feed a status message related to the present setting to the wireless communication element. The wireless communication element is arranged to transmit the status message to the data storage and processing system or to at least one electronic user device.

Abstract: A system for monitoring shopping baskets (e.g., baskets on human-propelled carts, motorized carts, or hand-carried baskets) can include a computer vision unit that can image a surveillance region (e.g., an exit to a store), determine whether a basket is empty or loaded with merchandise, and assess a potential for theft of the merchandise. The computer vision unit can include a camera and an image processor programmed to execute a computer vision algorithm to identify shopping baskets and determine a load status of the basket. The computer vision algorithm can comprise a neural network. The system can identify an at least partially loaded shopping basket that is exiting the store, without indicia of having paid for the merchandise, and execute an anti-theft action, e.g., actuating an alarm, notifying store personnel, activating a store surveillance system, activating an anti-theft device associated with the basket (e.g., a locking shopping cart wheel), etc.

Abstract: A vehicle traveling control apparatus includes an imaging device, a sensor, an information storage, a traveling road detector, an imaging height detector, and a control unit. The traveling road detector detects that a vehicle is traveling on a road satisfying a condition. The imaging height detector detects a distance from a surface of the road to the imaging device position. The control unit includes a separation height estimator that estimates a height of a separation part, based on a result of the imaging height detector and the preset imaging device position, and a sensor height estimator that estimates a distance from an upper surface of the separation part to the sensor position, based on a result of the separation height estimator and the preset sensor position. The control unit stops detection by the sensor if a value estimated by the sensor height estimator becomes a threshold or less.

Abstract: A multimodal vehicle can be configured according to the reference market and according to the user's needs, whether for shared or private use. The Multimodal Vehicle is created by a multimodal plug known as a TUC. The plug allows anchoring, with the utmost safety, the vehicle's on-board experiences inside the vehicle itself. Thanks to this system, it is possible to create a multimodal/modular platform, which can be configured in different dimensions. The platform provides available space wherein the user can move freely and insert, through the plug, the components that will make up the vehicle's interior, such as seats, dashboard, etc.

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: A processor coupled to memory is configured to receive image data based on an image captured by a camera of a vehicle. The image data is used as a basis of an input to a trained machine learning model trained to predict a three-dimensional trajectory of a machine learning feature. The three-dimensional trajectory of the machine learning feature is provided for automatically controlling the vehicle.

Abstract: A brake system for a motor vehicle may include at least one pressure supply device, formed by a hydraulic piston-cylinder unit driven by an electric motor, for hydraulic adjustment of a brake piston of at least one wheel brake, and at least one electromechanically actuatable wheel brake for electrical adjustment of a brake piston of a wheel brake. An electric motor and a first gearbox, which transmits the driving force of the electric motor to a further gearbox, are provided for electromechanical actuation of the wheel brake. The electromechanically actuatable wheel brake has a hydraulic control device having a piston-cylinder unit, the control piston of which serves for adjusting the brake piston and/or exerting a force on the brake piston. The control piston can be adjusted or a force can be exerted on the control piston.

Abstract: A track system of a vehicle can be monitored (e.g., during operation of the vehicle) to obtain information about the track system which can be used for various purposes, such as, for example, to convey the information about the track system to a user (e.g., an operator of the vehicle) and/or to control the vehicle, for instance, by controlling a speed of the vehicle depending on a state (e.g., a temperature and/or one or more other physical characteristics) of the track system. This may be useful, for example, to gain knowledge about a track of the track system, to help prevent rapid wear or other deterioration of the track of the track system (e.g., blowout), and/or to adapt how fast or slow the vehicle moves in order to protect the track of the track system while permitting the speed of the vehicle to be greater over short periods (e.g., when travelling on or crossing roads or other particular areas).

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.

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: A system for monitoring and controlling shopping cart usage comprises a wheel assembly that attaches to a shopping cart. In some embodiments 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: An inertia braking test system and a control method is provided, wherein the inertia braking test system is composed of an inertia brake test system, a sensor system and a tested object. An actuating device is connected with the inertia brake control device through a ball stud. The actuation function of the inertia brake control device with two degrees of freedom along the front-and-rear direction and the up-and-down direction of the vehicle is realized. The movable chassis realizes the mobile function of the system. The acceleration sensor can sense the acceleration of the movable chassis. Each force is tested by the first force sensor, the second force sensor and the third force sensor. The displacement data is measured by the first displacement sensor and the second displacement sensor, so that a movable brake system test is achieved.

Abstract: According to one embodiment a shopping cart includes an imaging unit configured to acquire images of a surface at a location of the shopping cart and a controller. The controller is configured to detect a boundary pattern in images acquired by the imaging unit. The boundary pattern is painted or drawn on the surface at a boundary between a first area and a second area. Based on the detected boundary pattern the controller determines whether the shopping cart has been moved from the first area to the second area or from the second area to the first area. The controller then controls mobility of the shopping cart based on whether the shopping cart has been moved from the first area to the second area or from the second area to the first area.

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.