Abstract: An aerial vehicle is programmed to proceed to a safe landing area upon a loss of GPS signals or other navigational signals. The aerial vehicle is programmed with a location of the safe landing area, and a visual descriptor of a landmark at the safe landing area. The landmark may be any natural or man-made structure or feature associated with the safe landing area, and the visual identifier may be any set of data corresponding to one or more contours, outlines, colors, textures, silhouettes or shapes of the landmark. Upon determining that a GPS position may not be determined, or shortly thereafter, the aerial vehicle proceeds on a course toward the location of the safe landing area, and begins to capture imaging data. The aerial vehicle confirms that it has arrived at the safe landing area upon detecting the visual identifier within the imaging data, and initiates a landing operation.

Abstract: Mobile platforms are used to capture an area using a variety of sensors (e.g., cameras and laser scanners) while traveling through the area, in order to create a representation (e.g., a navigable set of panoramic images, or a three-dimensional reconstruction). However, such sensors are often precisely calibrated in a controlled setting, and miscalibration during travel (e.g., due to a physical jolt) may result in a corruption of data and/or a recalibration that leaves the platform out of service for an extended duration. Presented herein are techniques for verifying sensor calibration during travel. Such techniques involve the identification of a sensor path for each sensor over time (e.g., a laser scanner path, a camera path, and a location sensor path) and a comparison of the paths, optionally after registration with a static coordinate system, to verify that the continued calibration of the sensors during the mobile operation of the platform.

Abstract: Mobile platforms are used to capture an area using a variety of sensors (e.g., cameras and laser scanners) while traveling through the area, in order to create a representation (e.g., a navigable set of panoramic images, or a three-dimensional reconstruction). However, such sensors are often precisely calibrated in a controlled setting, and miscalibration during travel (e.g., due to a physical jolt) may result in a corruption of data and/or a recalibration that leaves the platform out of service for an extended duration. Presented herein are techniques for verifying sensor calibration during travel. Such techniques involve the identification of a sensor path for each sensor over time (e.g., a laser scanner path, a camera path, and a location sensor path) and a comparison of the paths, optionally after registration with a static coordinate system, to verify that the continued calibration of the sensors during the mobile operation of the platform.

Abstract: Mobile platforms are used to capture an area using a variety of sensors (e.g., cameras and laser scanners) while traveling through the area, in order to create a representation (e.g., a navigable set of panoramic images, or a three-dimensional reconstruction). However, such sensors are often precisely calibrated in a controlled setting, and miscalibration during travel (e.g., due to a physical jolt) may result in a corruption of data and/or a recalibration that leaves the platform out of service for an extended duration. Presented herein are techniques for verifying sensor calibration during travel. Such techniques involve the identification of a sensor path for each sensor over time (e.g., a laser scanner path, a camera path, and a location sensor path) and a comparison of the paths, optionally after registration with a static coordinate system, to verify that the continued calibration of the sensors during the mobile operation of the platform.

Abstract: Mobile platforms are used to capture an area using a variety of sensors (e.g., cameras and laser scanners) while traveling through the area, in order to create a representation (e.g., a navigable set of panoramic images, or a three-dimensional reconstruction). However, such sensors are often precisely calibrated in a controlled setting, and miscalibration during travel (e.g., due to a physical jolt) may result in a corruption of data and/or a recalibration that leaves the platform out of service for an extended duration. Presented herein are techniques for verifying sensor calibration during travel. Such techniques involve the identification of a sensor path for each sensor over time (e.g., a laser scanner path, a camera path, and a location sensor path) and a comparison of the paths, optionally after registration with a static coordinate system, to verify that the continued calibration of the sensors during the mobile operation of the platform.