Systems and methods for navigating a vehicle within an environment are provided. In one aspect, a method comprises: (a) selecting, with aid of a processor, a subset of a plurality of sensors to be used for navigating the vehicle within the environment based on one or more predetermined criteria, wherein the plurality of sensors are arranged on the vehicle such that each sensor of the plurality of sensors is configured to obtain sensor data from a different field of view; (b) processing, with aid of the processor, the sensor data from the selected sensor(s) so as to generate navigation information for navigating the vehicle within the environment; and (c) outputting, with aid of the processor, signals for controlling the vehicle based on the navigation information.

Methods, systems, and apparatus, including computer programs encoded on a storage device, for using a drone to pre-surveil a portion of a property. In one aspect, a system may include a monitoring unit. The monitoring unit may include a network interface, a processor, and a storage device that includes instructions to cause the processor to perform operations. The operations may include obtaining data that is indicative of one or more acts of an occupant of the property, applying the obtained data that is indicative of one or more acts of the occupant of the property to a pre-surveillance rule, determining that the pre-surveillance rule is satisfied, determining a drone navigation path that is associated with the pre-surveillance rule, transmitting, to a drone, an instruction to perform pre-surveillance of the portion of the one or more properties using the drone navigation path.

Videography of surfaces and improved positional control of unmanned aerial vehicles (UAV) are disclosed. Embodiments include defining a plane relative a vertical or semi-vertical surface. Linearly scanning along a line parallel to the plane. The plane being defined by three non-colinear points. The linear scanning along the plane is defined by a defined distance from the plane to the surface. The scanning including distance sensor scanning. The distance sensor scanning creating a model of the surface. The distance sensor scanning can include sound-based or light-based distance measurement scanning. The surveillance scanning can further include capture of imagery of the surface along the linear scanning along the plane.

A method for determining position of a target includes determining at least two measurement points of the target, obtaining vector data of at least two direction vectors based on an imaging position of the target on an imaging system and parameter data of the imaging system, and determining a distance between the target and the imaging system according to the vector data and a current vertical height of the imaging system. Each of the at least two direction vectors is a vector from the imaging system to a corresponding one of the at least two measurement points.

The present disclosure relates to the field of augmented reality technology, and provides a display device that includes a display configured to display an image and a movement controller configured to control a movement state of the display device according to displacement instruction information such that the display and a target object conform to a mutual position relationship.

Systems and methods are provided for augmented reality during an automated site survey of a building using an unmanned aerial vehicle so that results of the site survey are substantially consistent, irrespective of whether the site survey is conducted when the building is bare or after systems and devices in the building are installed. Some methods can include retrieving a building information model of the building from a database device, receiving user input and, responsive thereto, transmitting navigation signals to the unmanned aerial vehicle to maneuver to a site survey position in the building and transmitting command signals to the unmanned aerial vehicle to conduct a RF test at the site survey position and return site survey results, and calculating signal degradation for the site survey position as a function of the site survey results and the building information model.

An unmanned vehicle (UV) navigation system is provided. The UV navigation system comprises a processor, a communication interface for communicating with a remote station, and a non-transitory memory device storing machine-readable instructions that, when executed by the processor, causes the processor to navigate the UV. The processor is configured to receive data from sensors, camera or data line for UV processor analysis, determine that a link-free trigger event has occurred, and autonomously navigate the UV in response to the trigger event.

Systems and methods for dynamically masking video or images captured by a drone device camera are provided. Such systems and methods include flying the drone device proximate to a potential surveillance area while in a learning mode, capturing first video or images of the potential surveillance area, identifying first privacy masking areas in the first video or images, flying the drone device proximate to an active surveillance area while in a standard mode, capturing second video or images of the active surveillance area, identifying second privacy masking areas in the second video or images, and dynamically masking a portion of the second video or images that contains any of the first privacy masking areas or the second privacy masking areas.

A virtual security network system can be used to prevent, deter or cease intrusion of an unauthorized person, animal or object into a secured area. The virtual security network system can include sensor units, a drone and a wide area network. Sensor units can be placed throughout a secured area and include a multitude of sensors with different capabilities that can detect a breach of the secured area. The drone can be mobilized upon receipt of a signal from a sensor unit when the secured area is breached to track an intruder. The drone can be equipped with pulsing lasers or a strobe light. The virtual security network system can also include a satellite, unmanned aerial vehicle, a launching and charging station for drone release and/or a drone fleet.

Techniques are described for an autonomous asset management system that integrates autonomous devices, such as drone devices and other robotic devices, with a home security system of a property to enable management, monitoring, and/or tracking of various assets located within the property. In some implementations, an indication of an asset associated with a property is obtained by an autonomous device. Sensor data collected by one or more sensors of the property is obtained by the autonomous device based on the indication of the asset. A present status of the asset is determined by the autonomous device based on the sensor data. A determination that the present status of the asset does not correspond to an expected status of the asset is made by the autonomous device. In response, the autonomous device navigates to the particular location of the property.