Abstract: Implementations of the present disclosure are generally directed to activating features in power machines. More particularly, implementations of the present disclosure are directed to remote activation of features in power machines.

Abstract: A materials handling vehicle includes: a power unit including: a steered wheel, and a steering device for generating a steer control signal; a load handling assembly coupled to the power unit; a controller located on the power unit for receiving the steer control signal; and a sensing device on the power unit and coupled to the controller. The sensing device monitoring areas in front of and next to the vehicle. Based on sensing device data, the controller may modify at least one of the following vehicle parameters: a maximum allowable turning angle or a steered-wheel-to-steering-device ratio.

Abstract: A detection system for determining an articulation angle between two sub-vehicles of a vehicle combination connected in an articulated manner includes a detection device configured to detect an environment, wherein the detection device is arranged on one of the sub-vehicles of the vehicle combination and a detection region of the detection device on a sub-region of a sub-vehicle connected to the one sub-vehicle in an articulated manner is oriented so that detection signals, which characterize the sub-region on the other sub-vehicle, can be generated by the detection device and output. The detection system further includes a processing unit configured to receive the detection signals and determine the articulation angle between the two sub-vehicles based on the detection signals and a projection device designed to image a predetermined pattern onto the sub-region on the other sub-vehicle to create a pattern image on the other sub-vehicle.

Abstract: An autonomous vehicle is disclosed that includes a velocity sensor; a radar system; a digital storage medium; and a controller in communication with the digital storage medium, radar system, and the velocity sensor. The controller, for example, may retrieve map data from the digital storage medium; receive current radar data from the radar system; receive autonomous vehicle velocity data from the velocity sensor; identify radar data points in the current radar data that represent objects in motion; remove radar data points from the current radar data that represent objects in motion; and/or match the radar data with the map data to return location data.

Abstract: A method includes determining a target specification map that is associated with a task and that indicates, for each respective region of a plurality of regions around a vehicle equipped with a sensor, a target value of a parameter of the sensor. The method also includes determining a capability specification map that indicates, for each respective region, an attained value of the parameter that the sensor is configured to provide. The method additionally includes comparing the capability specification map to the target specification map to determine, for each respective region, a disparity between the target value and the attained value. The method further includes, based on the comparing, identifying one or more of: a first subset of the plurality of regions where the target value exceeds the attained value or a second subset of the plurality of regions where the attained value meets or exceeds the target value.

Abstract: A route subdivision apparatus configured to subdivide a travel route for conducting work that includes: an area setting unit configured to set a plurality of work areas on a map; a route setting unit configured to set a scheduled route from a start point to an end point so that the scheduled route passes through consecutive first to third areas of the plurality of work areas; an entry/exit point setting unit configured to set an entry point and an exit point of the scheduled route in each work area; a boundary setting unit configured to set a boundary point between the exit point of the first area and the entry point of the second area and between the exit point of the second area and the entry point of the third area; and a distance calculation unit configured to calculate a length of a distance of each section divided by the boundary point on the scheduled route.

Abstract: In one aspect, an example method to be performed by a vehicle-based media system includes (a) receiving audio content; (b) causing one or more speakers to output the received audio content; (c) using a microphone of the vehicle-based media system to capture the output audio content; (d) identifying reference audio content that has at least a threshold extent of similarity with the captured audio content; (e) identifying a geographic location associated with the identified reference audio content; and (f) based at least on the identified geographic location associated with the identified reference audio content, outputting, via the user interface of the vehicle-based media system, a prompt to navigate to the identified geographic location.

Abstract: A method including detecting an obstacle location in response to an image, determining the obstacle location in response to a range measurement received from a range sensor, predicting a tow vehicle path in response to a tow vehicle steering angle and a tow vehicle location, predicting, by a processor, a trailer wheel path in response to the tow vehicle path, a vehicle dimension and a trailer dimension, and generating a warning control signal in response to an intersection of the obstacle location and the trailer wheel path.

Abstract: An unmanned aerial vehicle includes a camera, one or more sensors, memory storing first instructions that define an overall mission, and memory storing one or more mission cues. The vehicle further includes one or more processors configured to execute a first part of the first instructions to perform a first part of the overall mission. The processors are configured to process at least one of the image data and the sensor data to detect a presence of at least one of the mission cues. The processors are configured to, in response to detecting a mission cue, interrupting execution of the first instructions and executing second instructions to control the unmanned aerial vehicle to perform a first sub-mission of the overall mission. The processors are configured to after executing the second instructions, performing a second part of the overall mission by executing a second part of the first instructions.

Abstract: A first bias conversion unit converts, based on a first frequency and a second frequency, a signal bias related to carrier phase for correcting a carrier phase contained in a first ranging signal having the first frequency, to a signal bias related to carrier phase for correcting a carrier phase contained in a second ranging signal having the second frequency. A first correction unit corrects the carrier phase using the converted signal bias. A second bias conversion unit converts the signal bias related to pseudorange to the signal bias related to pseudorange by making reference to a conversion table indicating values for use in conversion of the signal bias related to pseudorange to the signal bias related to pseudorange. A second correction unit corrects a pseudorange using the converted signal bias.

Abstract: The present invention belongs to the technical field of control of aero-engines, and proposes an adaptive boosting algorithm-based turbofan engine direct data-driven control method. First, a turbofan engine controller is designed based on the Least Squares Support Vector Machine (LSSVM) algorithm, and further, the weight of a training sample is changed by an adaptive boosting algorithm so as to construct a turbofan engine direct data-driven controller combining a plurality of basic learners into strong learners. Compared with the previous solution only adopting LS SVM, the present invention enhances the control precision, improves the generalization ability of the algorithm, and effectively solves the problem of sparsity of samples by the adaptive boosting method. By the adaptive boosting algorithm-based turbofan engine direct data-driven control method designed by the present invention.

Abstract: A method for extracting changes in characteristics of a tire supporting a vehicle is provided. The method includes extracting selected tire characteristics from at least one sensor mounted on the tire. The selected tire characteristics are transmitted to a remote processor and are stored in a historical data log that is in communication with the remote processor. At least one tire characteristic of interest is selected, and a time series decomposition model is applied to data from the historical data log to delineate exogenous inputs from an underlying trend in the selected tire characteristic of interest. A learning model is applied to the underlying trend in the selected tire characteristic of interest to model a relationship between the selected tire characteristic of interest and a condition of the tire. A prediction value for a condition of the tire is output from the learning model.

Abstract: A return flight control method includes obtaining return-flight-evaluation information in a return flight mode, controlling an unmanned aerial vehicle (UAV) to return to an alternate landing area in response to that the return-flight-evaluation information satisfies a preset requirement, and controlling the UAV to return to a return point in response to that the return-flight-evaluation information does not satisfy the preset requirement.

Abstract: Methods, apparatus, systems and articles of manufacture are disclosed for vehicle steering to follow a curved path. An example apparatus includes interface circuitry to determine vehicle data of a vehicle, navigation manager circuitry to determine navigation data of the vehicle, and tracking mode controller circuitry to: determine the vehicle is approaching a curve based on the navigation data, in response to determining the vehicle is approaching a curve: determine a wheel steering angle utilizing the navigation data and the vehicle data, the wheel steering angle corresponding to the curve, determine a heading error offset adjustment utilizing the navigation data and the vehicle data, and generate steering commands based on the wheel steering angle and the heading error offset, the steering commands to control the vehicle to reduce control errors and follow the wheel steering angle.

Abstract: Various examples are directed to systems and methods for routing an autonomous vehicle. A vehicle autonomy system may generate first route data describing a first route for the autonomous vehicle to a first target location and control the autonomous vehicle using the first route data. The vehicle autonomy system may determine that the autonomous vehicle is within a threshold of the first target location and select a second target location associated with at least a second stopping location. The vehicle autonomy system may generate second route data describing a route extension of the first route from the first target location to the second target location and control the autonomous vehicle using the second route data.

Abstract: Among other things, we describe techniques for automatic annotation of environmental features in a map during navigation of a vehicle. The techniques include receiving, by the vehicle located within an environment, a map of the environment. Sensors of the vehicle receive sensor data and semantic data. The sensor data includes a plurality of features of the environment. A geometric model of a feature of the plurality of features is generated. The feature is associated with a drivable area within the environment. A drivable segment is extracted from the drivable area. The drivable segment is segregated into a plurality of geometric blocks, wherein each geometric block corresponds to a characteristic of the drivable area and the geometric model of the feature includes the plurality of geometric blocks. The geometric model is annotated using the semantic data. The annotated geometric model is embedded within the map.

Abstract: A materials handling vehicle includes: a power unit including: a steered wheel, and a steering device for generating a steer control signal; a load handling assembly coupled to the power unit; a controller located on the power unit for receiving the steer control signal; and a sensing device on the power unit and coupled to the controller. The sensing device monitoring areas in front of and next to the vehicle. Based on sensing device data, the controller may modify at least one of the following vehicle parameters: a maximum allowable turning angle or a steered-wheel-to-steering-device ratio.

Abstract: A control system for a vehicle including a first sensor that senses an acceleration of the vehicle and an electronic processor connected to the first sensor. The electronic processor determines whether a loading condition of the vehicle is detected and determines a first total mass of the vehicle using a first technique when the loading condition of the vehicle is detected. The electronic processor receives a first signal indicative of the acceleration of the vehicle from the first sensor, determines whether the acceleration of the vehicle is greater than zero, determines a second total mass of the vehicle using a second technique when the acceleration of the vehicle is greater than zero, determines a third total mass of the vehicle using a third technique when the acceleration of the vehicle is not greater than zero, and controls a function of the vehicle based on one of the total masses.

Abstract: Junction queueing for vehicles is described, in which vehicles may be queued based on arrival time at a junction, position relative to a stopping location at the junction, and/or an amount of time waiting for other vehicles to proceed through the junction (timeout). In some examples, the queue may be first generated based on the arrival times of any other vehicle relative to a particular vehicle generating the queue. The queue may be updated based on arrival times of other vehicles (e.g., after the particular vehicle), whether another vehicle has proceeded out-of-turn (e.g., based on a position at the junction), and/or a timeout for vehicles that wait for others to yield at the junction. In some examples, hysteresis and alterations of the score for safety reasons may alter queue order. The queue may be used to control the particular vehicle to traverse the junction.

Abstract: In a method for efficiently guiding a driver of a vehicle through intersections, information regarding status of one or more traffic lights positioned at one or more intersections is received by a computing device or system associated with the driver or vehicle. A value of speed for the vehicle that, if matched by the driver, causes the vehicle to arrive at the intersection while the traffic light is green and avoids stopping as the vehicle moves through the intersection, is calculated. A dynamic visual or audio indicator is caused, by the computing device or system, to be presented to the driver via a display or speaker, respectively, of the computing device or system. Causing the dynamic indicator to be presented to the driver includes setting the dynamic indicator based on the calculated value of speed.