Abstract: A photogrammetry system includes a memory, a processor, and a geo-positioning device. The geo-positioning device outputs telemetry regarding a vehicle on which one or more cameras are mounted. The processor can receive first telemetry from the geo-positioning device characterizing the vehicle telemetry at a first time, camera specification(s) regarding the cameras, photogrammetric requirement(s) for captured images, and a last camera trigger time. The processor can determine a next trigger time for the cameras based upon the received telemetry, camera specification(s), photogrammetric requirement(s), and last trigger time. The processor can transmit a trigger signal to the camera(s) and the geo-positioning device to cause the camera(s) to acquire images of a target and the geo-positioning device to store second vehicle telemetry data characterizing the vehicle telemetry at a second time that is after the first time and during acquisition of the images.

Abstract: A photogrammetry system includes a memory, a processor, and a geo-positioning device. The geo-positioning device outputs telemetry regarding a vehicle on which one or more cameras are mounted. The processor can receive first telemetry from the geo-positioning device characterizing the vehicle telemetry at a first time, camera specification(s) regarding the cameras, photogrammetric requirement(s) for captured images, and a last camera trigger time. The processor can determine a next trigger time for the cameras based upon the received telemetry, camera specification(s), photogrammetric requirement(s), and last trigger time. The processor can transmit a trigger signal to the camera(s) and the geo-positioning device to cause the camera(s) to acquire images of a target and the geo-positioning device to store second vehicle telemetry data characterizing the vehicle telemetry at a second time that is after the first time and during acquisition of the images.

Abstract: A photogrammetry system includes a memory, a processor, and a geo-positioning device. The geo-positioning device outputs telemetry regarding a vehicle on which one or more cameras are mounted. The processor can receive first telemetry from the geo-positioning device characterizing the vehicle telemetry at a first time, camera specification(s) regarding the cameras, photogrammetric requirement(s) for captured images, and a last camera trigger time. The processor can determine a next trigger time for the cameras based upon the received telemetry, camera specification(s), photogrammetric requirement(s), and last trigger time. The processor can transmit a trigger signal to the camera(s) and the geo-positioning device to cause the camera(s) to acquire images of a target and the geo-positioning device to store second vehicle telemetry data characterizing the vehicle telemetry at a second time that is after the first time and during acquisition of the images.

Abstract: System and methods may evaluate and/or improve target aiming accuracy for a sensor of an Unmanned Aerial Vehicle (“UAV”). According to some embodiments, a position and orientation measuring unit may measure a position and orientation associated with the sensor. A pose estimation platform may execute a first order calculation using the measured position and orientation as the actual position and orientation to create a first order model. A geometry evaluation platform may receive planned sensor position and orientation from a targeting goal data store and calculate a standard deviation for a target aiming error utilizing: (i) location and geometry information associated with the industrial asset, (ii) a known relationship between the sensor and a center-of-gravity of the UAV, (iii) the first order model as a transfer function, and (iv) an assumption that the position and orientation of the sensor have Gaussian-distributed noises with zero mean and a pre-determined standard deviation.

Abstract: System and methods may evaluate and/or improve target aiming accuracy for a sensor of an Unmanned Aerial Vehicle (“UAV”). According to some embodiments, a position and orientation measuring unit may measure a position and orientation associated with the sensor. A pose estimation platform may execute a first order calculation using the measured position and orientation as the actual position and orientation to create a first order model. A geometry evaluation platform may receive planned sensor position and orientation from a targeting goal data store and calculate a standard deviation for a target aiming error utilizing: (i) location and geometry information associated with the industrial asset, (ii) a known relationship between the sensor and a center-of-gravity of the UAV, (iii) the first order model as a transfer function, and (iv) an assumption that the position and orientation of the sensor have Gaussian-distributed noises with zero mean and a pre-determined standard deviation.