The present disclosure provides a method for detection of soil heavy metal pollution using an unmanned aerial vehicle (UAV) and an X-ray fluorescence (XRF) technology. Based. Based on hardware equipment such as the UAV, XRF analyzer, and embedded equipment, the present disclosure develops an altitude hold module of the system and a ground-contact monitoring module, and assists the UAV to achieve safe and accurate fixed-point hovering, and develops a driving device for data acquisition to replace manual control and realize the automatic acquisition of XRF data. The data inversion method is realized by using embedded equipment, and after the data is acquired by the portable XRF analyzer near the ground, the algorithm research of inversion processing of contents of heavy metal elements in soil is realized, such that the portable XRF analyzer can automatically and accurately detect the contents of heavy metals in soil at a certain distance.

The present disclosure provides a method for detection of soil heavy metal pollution using an unmanned aerial vehicle (UAV) and an X-ray fluorescence (XRF) technology. Based. Based on hardware equipment such as the UAV, XRF analyzer, and embedded equipment, the present disclosure develops an altitude hold module of the system and a ground-contact monitoring module, and assists the UAV to achieve safe and accurate fixed-point hovering, and develops a driving device for data acquisition to replace manual control and realize the automatic acquisition of XRF data. The data inversion method is realized by using embedded equipment, and after the data is acquired by the portable XRF analyzer near the ground, the algorithm research of inversion processing of contents of heavy metal elements in soil is realized, such that the portable XRF analyzer can automatically and accurately detect the contents of heavy metals in soil at a certain distance.

Methods for commissioning a construction vehicle for machine control operations are provided. A GNSS receiver configured for determining position information, tilt information, and heading information is coupled to a rigid member of the construction vehicle. The commissioning process provides parameters that can be used for tracking and controlling movement of an implement coupled to the construction vehicle during the machine control operations.

A system and method established and maintains precision relative position, navigation, and timing (PNT) across a network of at least four mutually connected mobile platforms. In embodiments, a key (e.g., advantaged, absolute positioning capable) node of the network determines its pressure altitude and inertial state relative to its platform reference frame and receives inertial state and pressure altitude data from each neighboring node (in exchange for its own) to estimate the relative position and orientation of each neighbor node in its platform frame. The key node performs ranging to each neighboring node, and the neighboring nodes additionally range between each other and exchange ranging data with the key node. By correcting position and orientation estimates via ranging data, the key node determines and maintains extended relative PNT (e.g., in GPS-denied areas), which relative PNT solution is distributed across all network nodes.

Aspects of the subject disclosure may include, for example, a process that determines a current location of a mobile device according to a horizontal reference, obtains a corresponding barometric pressure reading at the current location of the mobile device, and determines a current position of the mobile device according to the current location of the mobile device and the corresponding barometric pressure reading. A historical record of positions of the mobile device is updated according to the current position of the mobile device and other positions of the mobile device determined at other times, and a historical record of positions of the mobile device to a map of a facility is updated to obtain a referenced pattern of movement of the mobile device within the facility. Other embodiments are disclosed.

Aspects of the subject disclosure may include, for example, a process that determines a current location of a mobile device according to a horizontal reference, obtains a corresponding barometric pressure reading at the current location of the mobile device, and determines a current position of the mobile device according to the current location of the mobile device and the corresponding barometric pressure reading. A historical record of positions of the mobile device is updated according to the current position of the mobile device and other positions of the mobile device determined at other times, and a historical record of positions of the mobile device to a map of a facility is updated to obtain a referenced pattern of movement of the mobile device within the facility. Other embodiments are disclosed.

A system for autonomous mower navigation includes a robotic golf greens mower, an RTK-GPS base for providing RTK-GPS correction data, a cloud based data processing service for processing geolocation data, one or more computer servers, one or more mobile devices, a data communications network for providing communications access between any of the RTK-GPS base, the mobile device, the cloud service, and the robotic greens mower. The RTK-GPS correction data is processed by the cloud service and provided to the robotics greens mower via the data communications network.

Provided is a navigation board, a multi-source data fusion method for a navigation board and a transporter. The navigation board includes a printed circuit board, a global navigation satellite system module, an inertial sensor, a processor, and a data interface; the processor is configured to execute a large misalignment angle initialization algorithm, an inertial strapdown solution algorithm, and a multi-source data fusion solution; and a size of the navigation board is smaller than or equal to a size of a standard GNSS board, and the navigation board at least includes the same data interface as a data interface of the standard GNSS board.

In one embodiment, a method includes accessing global positioning system (GPS) data indicating a raw location associated with the computing system; accessing, based on the raw location, environmental model data including one or more structures; generating GPS correction data by processing the GPS data and the environmental model data using a machine-learning (ML) model that has been trained to compensate inaccurate GPS readings due to environmental interference; and determining an accurate location by correcting the raw location using the GPS correction data.

In one embodiment, a method includes accessing global positioning system (GPS) data indicating a raw location associated with the computing system; accessing, based on the raw location, environmental model data including one or more structures; generating GPS correction data by processing the GPS data and the environmental model data using a machine-learning (ML) model that has been trained to compensate inaccurate GPS readings due to environmental interference; and determining an accurate location by correcting the raw location using the GPS correction data.