Abstract: Systems, methods, and apparatus for sensor fault detection and identification using residual failure pattern recognition are disclosed. In one or more embodiments, a method for sensor fault detection and identification for a vehicle comprises sensing, with sensors located on the vehicle, data. The method further comprises performing majority voting on the data for each of the types of data to generate a single voted value for each of the types of data. Also, the method comprises generating, for each of the types of data, estimated values by using some of the voted values. In addition, the method comprises generating residuals by comparing the estimated values to the voted values. Further, the method comprises analyzing a pattern of the residuals to determine which of the types of the data is erroneous to detect and identify a fault experienced by at least one of the sensors on the vehicle.

Abstract: A system includes a memory and a processor. The memory is configured to store map data indicating positions of landmarks. The processor is configured to receive image data from an image sensor. The processor is also configured to determine, based on the image data, a first estimate of a position, relative to the image sensor, of a landmark identified in the map data. The processor is configured to determine orientation of the image sensor based on inertial measurement unit measurements. The processor is also configured to determine, based on position information, the orientation, and the map data, a second estimate of the position of the landmark. The processor is configured to determine position offset data based on a comparison of the first estimate and the second estimate. The processor is also configured to generate, based on the position offset data and the position information, an output indicating an adjusted position.

Abstract: Example implementations relate to autonomous airport runway navigation. An example system includes a first sensor and a second sensor coupled to an aircraft at a first location and a second location, respectively, and a computing system configured to receive sensor data from one or both of the first sensor and the second sensor to detect airport markings positioned proximate a runway. The computing system is further configured to identify a centerline of the runway based on the airport markings and receive sensor data from both of the first sensor and the second sensor to determine a lateral displacement that represents a distance between a reference point of the aircraft and the centerline of the runway. The computing system is further configured to control instructions that indicate adjustments for aligning the reference point of the aircraft with the centerline of the runway during subsequent navigation of the aircraft.

Abstract: Systems, methods, and apparatus for sensor fault detection and identification using residual failure pattern recognition are disclosed. In one or more embodiments, a method for sensor fault detection and identification for a vehicle comprises sensing, with sensors located on the vehicle, data. The method further comprises performing majority voting on the data for each of the types of data to generate a single voted value for each of the types of data. Also, the method comprises generating, for each of the types of data, estimated values by using some of the voted values. In addition, the method comprises generating residuals by comparing the estimated values to the voted values. Further, the method comprises analyzing a pattern of the residuals to determine which of the types of the data is erroneous to detect and identify a fault experienced by at least one of the sensors on the vehicle.

Abstract: A system includes a memory and a processor. The memory is configured to store map data indicating positions of landmarks. The processor is configured to receive image data from an image sensor. The processor is also configured to determine, based on the image data, a first estimate of a position, relative to the image sensor, of a landmark identified in the map data. The processor is configured to determine orientation of the image sensor based on inertial measurement unit measurements. The processor is also configured to determine, based on position information, the orientation, and the map data, a second estimate of the position of the landmark. The processor is configured to determine position offset data based on a comparison of the first estimate and the second estimate. The processor is also configured to generate, based on the position offset data and the position information, an output indicating an adjusted position.

Abstract: Closed loop control of control surfaces is described herein. One disclosed example method includes measuring a flight metric of an aircraft during flight and calculating, using a processor, a deflection of a control surface of the aircraft based on the flight metric. The disclosed example method also includes adjusting the deflection to an effective deflection level based on the calculated deflection to reduce a drag coefficient of the aircraft.

Abstract: Closed loop control of control surfaces is described herein. One disclosed example method includes measuring a flight metric of an aircraft during flight and calculating, using a processor, a deflection of a control surface of the aircraft based on the flight metric. The disclosed example method also includes adjusting the deflection to an effective deflection level based on the calculated deflection to reduce a drag coefficient of the aircraft.

Abstract: An apparatus for controlling the formation flight of a trailing aircraft relative to a vortex generated by a leading aircraft includes a position module, peak-seeking module, limiter module, and control module. The position module is configured to determine a position of the vortex relative to the trailing aircraft. The peak-seeking module is configured to determine a desired position of the trailing aircraft for providing desired vortex-induced aerodynamic benefits based on the position of the vortex relative to the trailing aircraft and a mapping function of an individual performance metric. The limiter module is configured to modify the desired position of the trailing aircraft to avoid unintended crossings of the trailing aircraft into the vortex. Finally, the control module is configured to control flight of the trailing aircraft based on one of the desired position of the trailing aircraft and modified desired position of the trailing aircraft.