Abstract:
A method (400) of additively manufacturing a composite part (102) is disclosed. The method (400) comprises depositing, via a delivery guide (112), a segment (120) of a continuous flexible line (106) along a print path (122). The continuous flexible line (106) comprises a non-resin component (108) and a thermosetting-epoxy-resin component (110) that is partially cured. The method (400) also comprises maintaining the thermosetting-epoxy-resin component (110) of at least the continuous flexible line (106) being advanced toward the print path (122) via the delivery guide (112) below a threshold temperature. The method (400) further comprises delivering a predetermined or actively determined amount of curing energy (118) to the segment (120) of the continuous flexible line (106) at a controlled rate while advancing the continuous flexible line (106) toward the print path (122) to at least partially cure the segment (120) of the continuous flexible line (106).
Abstract:
A method (400) of additively manufacturing a composite part (102) comprises pushing a continuous flexible line (106) through a delivery guide (112). The continuous flexible line comprises (106) a non-resin component (108) and a photopolymer-resin component (110) that is partially cured. The method (400) also comprises depositing, via the delivery guide (112), a segment (120) of the continuous flexible line (106) along a print path (122). Additionally, the method (400) comprises delivering curing energy (118) at least to a portion (124) of the segment (120) of the continuous flexible line (106) deposited along the print path (122).
Abstract:
In accordance with one or more aspects of the disclosed embodiment, a system for transporting wire components during the assembly of wire bundles includes an air-operated tube network connecting a transport source station to a plurality of transport destination stations, the air-operated tube network comprising a junction coupled between the transport source station and the plurality of transport destination stations, and a system controller that includes a wire bundle assembly program, the system controller programmed to automatically transmit wire components from the source station to at least one of the transport destination stations based on the wire bundle assembly program.
Abstract:
Systems and methods for autonomous vehicle path planning are described herein. An example vehicle includes an image sensor to obtain an image of a scene of an area surrounding the vehicle. The vehicle also includes navigation system circuitry to: analyze the image and generate a semantically segmented image that identifies one or more types of features in the image; project the semantically segmented image to a two-dimensional (2D) map projection; convert the 2D map projection into a cost map; and determine a path for the vehicle based on the cost map.
Abstract:
A method including executing a logical computing element (LCE) on a server. Worker LCEs are executed on the server. A first electronic file comprising geometry data in a first data structure is received at the controller LCE. An available worker LCE is identified, by the controller LCE, as an in-use worker LCE from among the worker LCEs. The geometry data is imported by the in-use worker LCE. A job instance is established by the in-use worker LCE. A rendering engine is launched by the in-use worker LCE. The rendering engine generates, for the job instance and using the geometry data, a dataset file in a second data structure different than the first data structure. The dataset file is returned by the in-use worker LCE to the controller LCE. The dataset file is returned by the controller LCE to a remote computer.
Abstract:
Solutions are provided for auto-labeling sensor data for machine learning (ML). An example includes: determining a platform's own position; recording, from a sensor aboard the platform, sensor data comprising a sensor image; receiving position data for at least one intruder object (e.g., a nearby airborne object); based at least on the position data for the intruder object and the platform's position, determining a relative position and a relative velocity of the intruder object; based at least on the relative position and a relative velocity of the intruder object and a field of view of the sensor, determining an expected position of the intruder object in the sensor image; labeling the sensor image, wherein the labeling comprises annotating the sensor image with a region of interest and an object identification; and training an artificial intelligence (AI) model using the labeled sensor image.
Abstract:
In an example, a method is described. The method includes causing one or more sensors arranged on an aircraft to acquire, over a window of time, first data associated with a first object that is within an environment of the aircraft, where the one or more sensors include one or more of a light detection and ranging (LIDAR) sensor, a radar sensor, or a camera, causing an array of microphones arranged on the aircraft to acquire, over approximately the same window of time as the first data is acquired, first acoustic data associated with the first object, and training a machine learning model by using the first acoustic data as an input value to the machine learning model and by using an azimuth, a range, an elevation, and a type of the first object identified from the first data as ground truth output labels for the machine learning model.
Abstract:
A method for aligning a removable sensor on a vehicle includes connecting the removable sensor to a sensor mounting device. The method further includes connecting a connector of an alignment apparatus to either (i) the removable sensor such that a spatial reference component of the alignment apparatus has a known position and orientation relative to a current position and orientation of the removable sensor or (ii) a fixed connection location on the vehicle such that the spatial reference component indicates a desired position and orientation of the removable sensor. In addition the method includes adjusting the current position and orientation of the removable sensor by reference to the alignment apparatus to cause the current position and orientation of the removable sensor to match the desired position and orientation of the removable sensor.
Abstract:
In an example, a method is described. The method includes causing one or more sensors arranged on an aircraft to acquire, over a window of time, first data associated with a first object that is within an environment of the aircraft, where the one or more sensors include one or more of a light detection and ranging (LIDAR) sensor, a radar sensor, or a camera, causing an array of microphones arranged on the aircraft to acquire, over approximately the same window of time as the first data is acquired, first acoustic data associated with the first object, and training a machine learning model by using the first acoustic data as an input value to the machine learning model and by using an azimuth, a range, an elevation, and a type of the first object identified from the first data as ground truth output labels for the machine learning model.
Abstract:
A wire guide and a laser wire-processing device that includes a wire guide are provided. The laser wire-processing device includes a housing and an aperture in a side of the housing, wherein the aperture defines a longitudinal axis that is substantially perpendicular to the aperture. The laser wire-processing device also includes a backstop arranged in the housing and aligned with the longitudinal axis, the backstop defining a wire-contact surface in a facing relationship with the aperture. The laser wire-processing device also includes a wire guide arranged in the housing to manipulate a wire inserted through the aperture into a desired position relative to the longitudinal axis between the aperture and the backstop. The laser wire-processing device also includes a laser operable to direct a laser beam toward an insulation layer of the wire. The wire guide could be a tube arranged in the device or a backstop guide.