A marine drone system utilizing an unmanned aerial vehicle to provide visual feedback for conditions including temperature, depth, and conditions which may suggest favorable fishing conditions, such as weed lines, flotsam, breaks, and objects, such as birds or fish. The system utilizes a plurality of sensors, including, but not limited to, cameras, laser, GPS, radar, and LIDAR. The visual feedback may be shown as a video fees or a map, wherein the feedback is shown as a visual backgrounds, wherein an overlay of interactive functions provides information regarding the conditions. The system also includes method steps for implementing, obtaining, and displaying the information. The system hardware includes the unmanned aerial vehicle, a base station, and a hardwired tether between the unmanned aerial vehicle and the base station providing power and bi-directional data transfer.

An imaging system can include a first and second camera configured to capture first and second sets of oblique images along first and second scan paths, respectively, on an object area. A drive is coupled to a scanning mirror structure, having at least one mirror surface, and configured to rotate the structure about a scan axis based on a scan angle. The first and second cameras each have an optical axis set at an oblique angle to the scan axis and include a respective lens to focus first and second imaging beams reflected from the mirror surface to an image sensor located in each of the cameras. The first and second imaging beams captured by their respective cameras can vary according to the scan angle. Each of the image sensors captures respective sets of oblique images by sampling the imaging beams at first and second values of the scan angle.

Systems and methods for service drone landing zone operations are disclosed herein. An example method includes determining location-specific information for a location, the location-specific information including at least images of the location from at least one of a vehicle or a mobile device at the location, determining a landing area for a drone at the location using the location-specific information. receiving localizing signals from at least one of the vehicle or the mobile device as the drone approaches the location, and causing the drone to land in the landing area using the localizing signals.

Implementations are described herein for localizing individual plants by aligning high-elevation images using invariant anchor points while disregarding variant feature points, such as deformable plants. High-elevation images that capture the plurality of plants at a resolution at which wind-triggered deformation of individual plants is perceptible between the high-elevation images may be obtained. First regions of the high-elevation images that depict the plurality of plants may be classified as variant features that are unusable as invariant anchor points. Second regions of the high-elevation images that are disjoint from the first set of regions may be classified as invariant anchor points. The high-elevation images may be aligned based on invariant anchor point(s) that are common among at least some of the high-elevation images. Based on the aligned high-elevation images, individual plant(s) may be localized within one of the high-elevation images for performance of one or more agricultural tasks.

Techniques for range finding for an unmanned aerial system are described. As one example, an unmanned aerial system includes at least one motor to provide propulsion, a piezoelectric acoustic actuator having a resonant frequency, a piezoelectric acoustic sensor having the resonant frequency, and a controller to modulate a fixed amplitude and fixed frequency, at the resonant frequency, carrier wave according to a pseudo-random sequence of bits to produce a modulated wave sequence having a respective section of the carrier wave for each bit of the bits of the pseudo-random sequence having a first value, and a respective section of the carrier wave for each bit of the bits of the pseudo-random sequence having a second value, transmit the modulated wave sequence from the piezoelectric acoustic actuator, receive a reflected wave sequence including a reflection of the modulated wave sequence with the piezoelectric acoustic sensor, determine a delay time between the transmit and the receive of the modulated wave sequence based on the reflected wave sequence received by the piezoelectric acoustic sensor and the modulated wave sequence transmitted by the piezoelectric acoustic actuator, and modify power provided to the at least one motor based on the delay time.

An automatic parking lot management system includes an infrastructure sensor for detecting a preset range in a parking lot. A mobile body including a peripheral detection sensor is used, and the mobile body is able to be moved to a detectable position at which the peripheral detection sensor of the mobile body is able to detect a detection range of the infrastructure sensor. When determination is made that there is an abnormality in the infrastructure sensor, the mobile body is moved to the detectable position to cause the peripheral detection sensor to detect the detection range of the infrastructure sensor.

A camera payload configured for attachment to an unmanned aerial system with a payload interface. The camera payload includes a payload interface that includes a configuration that is structured and arranged to provide tool-free mechanical retention, electrical connections for power, and electrical connections for data; at least one camera mounted in the camera payload; at least one composite skin and at least one internal structure; at least one sealable and removable camera window retained on an outside of the camera payload; and at least one computer arranged within the camera payload.

A mapping system for multiview video displays presents an interactive map comprising a plurality of regularly distributed grid points indicating availability of multiview display data at those grid points. When selected, each of the grid points present a plurality of videos, images, and other data collected that are available for display.

A method includes receiving a digital surface model of an area for unmanned aerial vehicle (UAV) navigation. The digital surface model represents an environmental surface in the area. The method includes determining, for each grid cell of a plurality of grid cells in the area, a confidence value of an altitude of the environmental surface at the grid cell and determining a terrain clearance value based at least on the confidence value of the altitude of the environmental surface at the grid cell. The method includes determining a route for a UAV through the area such that the altitude of the UAV is above the altitude of the environmental surface at each grid cell of a sequence of grid cells of the route by at least the terrain clearance value determined for the grid cell. The method includes causing the UAV to navigate through the area using the determined route.

A survey system for accurately surveying an area includes a coordinate acquisition section that acquires a set of three-dimensional coordinates of a survey point or a base station used for determining sets of coordinates of the area, as a set of measurement coordinates, a comparative coordinate acquisition section that acquires at least a height-direction coordinate value of a set of comparative coordinates indicating a position within a predetermined range from the acquired set of measurement coordinates; and a determining section that calculates a difference between a height-direction coordinate value of the set of measurement coordinates and the height-direction coordinate value of the set of comparative coordinates and determines that at least any one of the set of measurement coordinates and the set of comparative coordinates are incorrect when the difference is larger than a predetermined value.