A method for loading an Unmanned Aerial Vehicle with one or more items is disclosed. The method includes positioning one or more items in specific positions within one of the Unmanned Aerial Vehicle and a container configured to be carried by the Unmanned Aerial Vehicle based on a Center of Gravity of each of the one or more items. The method also includes securing the one or more items in the specific positions within the one of the Unmanned Aerial Vehicle and the container to prevent the one or more items from shifting and changing a combined Center of Gravity of the one or more items combined with the one of the Unmanned Aerial Vehicle and the container during a flight of the Unmanned Aerial Vehicle.

A method for loading an Unmanned Aerial Vehicle with one or more items is disclosed. The method includes determining a Center of Gravity of each of the one or more items. The method also includes matching a combined Center of Gravity of the one or more items with a Center of Gravity of the Unmanned Aerial Vehicle.

A method for loading one of an Unmanned Aerial Vehicle (UAV) and a container for the Unmanned Aerial Vehicle with one or more items is disclosed. The method includes determining a Center of Gravity (COG) of the one or more items. The method also includes loading the one of the UAV and the container for the UAV with the one or more items based on the COG of the one or more items. The method further includes positioning one or more weights relative to the one or more items and relative to the one of the UAV and the container for the UAV such that a combined COG of the one or more items, the one of the UAV and the container for the UAV, and the one or more weights is positioned within a predetermined region relative to the one of the UAV and the container for the UAV.

A method for loading an Unmanned Aerial Vehicle with multiple items is disclosed. The method includes determining a weight, size, and Center of Gravity of each of the multiple items. The method also includes positioning the multiple items relative to one another such that a combined Center of Gravity of the multiple items will be positioned within a predetermined region. The method further includes loading the multiple items onto the Unmanned Aerial Vehicle with the combined Center of Gravity of the multiple items positioned within the predetermined region.

A method converts an aircraft takeoff trim setting that would be a function of several parameters to a value that is a function of CG position only. In this way, it is possible to create a direct simple equivalence between Stabilizer angle and CG. The equivalent CG can be presented in real time to the pilot.

A weight distribution associated with an unmanned aerial vehicle (UAV) may be determined prior to dispatch of the UAV and/or after the UAV returns from operation (e.g., a flight). In some embodiments, one or more UAVs may be placed on or proximate to a physical metrics acquisition (PMA) device. The PMA device may include a configurable scale and may be used to determine a distribution of weight of the UAV at three or more points associated with the UAV. The distribution of weight may be used generate analytics, which may include a total weight of a vehicle, a center of mass of the vehicle (in two or more dimensions), power requirements of the UAV for a given flight task (e.g., how much battery power the UAV requires, etc.), and/or other analytics. In various embodiments, the PMA device may perform moment of inertia tests for the UAV.

A system for weight measurement for an aircraft having a weight on wheels threshold between a flight mode and a ground mode includes a weight on wheels sensor arrangeable on a landing gear assembly of the aircraft, and a computing device receiving first detected data from the sensor related to strain on the landing gear assembly. The computing device calculates a rate of change of the strain over time to determine when the landing gear assembly reaches the weight on wheels threshold. The system also measures aircraft gross weight in a static condition.

A weight estimation system for estimating weight of an aerospace vehicle while grounded, the weight estimation system comprising a measurement subsystem including at least one sensor configured to measure a physical property in an interface that interfaces at least one of a fuselage and a wing with an undercarriage of said aerospace vehicle, in at least one area exhibiting a measurable change in geometry that is at least partly due to said weight, said measurement subsystem configured to produce measured data indicative of said weight of said aerospace vehicle; and a processor for receiving at least part of said measured data, said processor configured to estimate said weight, by relating said measured data with predetermined physical-property-to-weight correspondence data associated with said aerospace vehicle.

The present invention provides a large-scale high-speed rotary equipment measuring and intelligent learning assembly method and device based on vector minimization geometry center, mass center, the center of gravity and the center of inertia, belonging to the technical field of mechanical assembly. The method includes the steps of establishing a four-parameter circular profile measuring model for a single stage of rotor, simplifying the established four-parameter circular profile measuring model for the single stage of rotor, and establishing a four-target optimization model of the geometry center, mass center, the center of gravity and the center of inertia of multiple stages of rotors based on the angular orientation mounting position of each stage of rotor. The device include a base, an air flotation shaft system, an aligning and tilt regulating workbench, precise force sensors, a static balance measuring platform, an upright column, a lower transverse measuring rod, a lower telescopic inductive sensor, an upper transverse measuring rod and an upper lever type inductive sensor.

Methods of determining a final space reservation for a new aircraft are disclosed. The methods include using parametric definitions of potential payloads to generate a population of representative payloads for use in creating an initial space reservation. The methods include accounting for and applying a variety of margins on each potential payload and taking the union of potential payloads. Alternatively, the union can be taken first and then the margins applied. A homogenous space reservation can be determined based upon a variety of differently shaped or sized payloads, including a margin build-up to mitigate risk of unknowns associated with future changes in specific payload shapes and sizes, build tolerances, environmental conditions, and/or loading and unloading motions and clearances. Once this space reservation is known, it is possible to design an external shape of a carrying vehicle by staying outside of this space reservation.