Methods, systems, and devices for data capture trigger configuration for asset tracking are provided. Another example method capturing raw data involves obtaining a rich data capture trigger that defines when a controller of an asset tracking device onboard an asset is to identify and log an unsimplified block of raw data in raw data on the asset tracking device for rich data analysis, transmitting data capture instructions to the asset tracking device that contains the rich data capture trigger, and receiving the simplified set of raw data and the unsimplified block of raw data from the asset tracking device.

This document describes “Multi-domain Neighborhood Embedding and Weighting” (MNEW) for use in processing point cloud data, including sparsely populated data obtained from a lidar, a camera, a radar, or combination thereof. MNEW is a process based on a dilation architecture that captures pointwise and global features of the point cloud data involving multi-scale local semantics adopted from a hierarchical encoder-decoder structure. Neighborhood information is embedded in both static geometric and dynamic feature domains. A geometric distance, feature similarity, and local sparsity can be computed and transformed into adaptive weighting factors that are reapplied to the point cloud data. This enables an automotive system to obtain outstanding performance with sparse and dense point cloud data. Processing point cloud data via the MNEW techniques promotes greater adoption of sensor-based autonomous driving and perception-based systems.

Methods, apparatus, and articles of manufacture to generate acquisition paths are disclosed. An example apparatus includes input interface circuitry to obtain input data associated with a vehicle, threshold calculation circuitry to calculate, based on the input data, a threshold curvature and a threshold curvature rate of the vehicle, and acquisition path generation circuitry to select a point on a target path of the vehicle, generate an acquisition path from a current position of the vehicle to the point, the acquisition path including at least two curves, and cause storage of the acquisition path in response to the at least two curves satisfying the threshold curvature and the threshold curvature rate.

A control system for an autonomous work vehicle includes a controller configured to obtain map data for an area that the autonomous work vehicle is traversing, wherein the map data includes mapped landmarks. The controller is configured to determine a current position of the autonomous work vehicle in the area based on feedback from at least a first sensor and to determine a distance between a landmark in the area from the autonomous work vehicle based on feedback from at least a second sensor and the current position of the autonomous work vehicle. The controller is configured to determine a difference between the distance and an estimated distance between the autonomous work vehicle and the landmark based on the map data and the current position of the autonomous work vehicle. The controller is configured to determine whether the landmark is accurately mapped in the map data.

A ground utility robot and implement attachment apparatus having a ground utility robot, at least one implement, at least one solar panel, at least one battery that is chargeable by the at least one solar panel, a power take-off system that is connected to the ground utility robot and to the at least one implement; where the battery powers said ground utility robot and the implement; a safety system that has a computer, a safety program that utilizes a processing logic on the computer, where the safety program initiates precautionary measures that are carried out by the ground utility robot and the power take-off system if an object comes within a predefined distance from the ground utility robot and implement attachment apparatus.

This provides methods and systems for the global navigation satellite system (GNSS) combined with the dead-reckoning (DR) technique, which is expected to provide a vehicle positioning solution, but it may contain an unacceptable amount of error due to multiple causes, e.g., atmospheric effects, clock timing, and multipath effect. Particularly, the multipath effect is a major issue in the urban canyons. This invention overcomes these and other issues in the DR solution by a geofencing framework based on road geometry information and multiple supplemental kinematic filters. It guarantees a road-level accuracy and enables certain V2X applications which does not require sub-meter accuracy, e.g., signal phase timing, intersection movement assist, curve speed warning, reduced speed zone warning, and red-light violation warning. Automated vehicle is another use case. This is used for autonomous cars and vehicle safety, shown with various examples/variations.

This work vehicle has: a positioning unit for measuring the current position and the current direction of the vehicle body using a satellite positioning system; and an automatic travel control unit for executing automatic travel control based on positioning information from the positioning unit. The positioning unit comprises: a plurality of positioning antennas provided on the vehicle body; a plurality of positioning units for measuring the positions of the positioning antennas; a calculation unit for calculating the current position and the current direction of the vehicle body on the basis of positioning information from the positioning units; and a positioning state determination unit for determining whether or not the positioning state of the positioning units is a high-accuracy positioning state. When at least two positioning units are in the high accuracy positioning state, the positioning state determination unit permits the start of the automatic travel control.

This automatic travel system for a work vehicle is provided with: a position information obtaining unit; and an automatic travel control unit that causes a work vehicle to automatically travel along a target path. The automatic travel control unit sets a control target position on the target path including a plurality of work paths arranged in parallel with each other and a plurality of turning paths that connect the work paths in an order of travel of the work vehicle, to enable automatic travel of the work vehicle along the target path. The automatic travel control unit, when the work vehicle is positioned on a work path in the vicinity of a boundary with a turning path, sets the control target position on an extension of the work path. The automatic travel control unit, when the work vehicle is positioned on a turning path in the vicinity of a boundary with a work path, sets the control target position on the work path.

This work information management device includes: a tractor-side information acquisition unit for acquiring tractor-side information which includes position information of a tractor at each of specific times and operation information of the tractor at each of specific times, such tractor-side information being acquired from the tractor having mounted thereon any one of a plurality of types of work machines; and a work type estimation unit for estimating the work type of work that has been carried out by a work machine mounted on the tractor, on the basis of the tractor-side information acquired by the tractor-side information acquisition unit.

A system and method for marking a boundary while defining an autonomous worksite includes receiving first information indicative of a first maneuvering distance from a side of a machine and activating an indicator. The indicator, representative of the first maneuvering distance, is positioned at the side of the machine to be visible to an operator of the machine. The machine is positioned on a worksite surface along a path to be traversed when executing a work plan. After a control system receives a verification from the operator that the machine may operate outside the worksite area and within an outer boundary defined by the first maneuvering distance, a worksite perimeter is defined to include the path, and a geofence for the machine is determined to substantially overlay the outer boundary.