A method for planning sample points for surveying and mapping is disclosed, which includes: acquiring a reference photographing location point corresponding to a region to be surveyed and mapped, and establishing a mapping relation between one shooting point in a combined shooting point set and the reference photographing location point; determining a plurality of auxiliary photographing location points corresponding to the reference photographing location point based on the mapping relation preset relative positional relations between the shooting points in the combined shooting point set; and using the reference photographing location point and the plurality of auxiliary photographing location points as sample points for surveying and mapping based on which an unmanned aerial vehicle for surveying and mapping performs surveying and mapping in the region to be surveyed and mapped. An apparatus for planning sample points for surveying and mapping, a control terminal, and a storage medium are also disclosed.

Improvements in secure communication using drones. The communication uses aircraft to provide a secure communication link that prevents undesirable reception. The secure link can be between two people, groups or more specific people. Optical transmission can be from laser, infrared, ultraviolet, white light or a particular wavelength of light. One or multiple of aircraft to relay information between senders and receivers. The aircraft can be drones that operate within buildings or with overhead aircraft. The aircraft can intelligently follow or lead a person to maintain a line-of-sight. Each user can have their own tracking aircraft and the aircraft can communicate between each other using light and/or wireless communication to optimize line-of-sight between the aircraft over geographic medium. The geographic medium may include one or more of terrain, air, water, and space. The object may be a soldier, vehicle, drone, or ballistic.

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.

Provided herein is a continuously unmanned multi-phenomenon sensor system and a continuously unmanned multi-phenomenon sensor platform comprising a plurality of continuously unmanned multi-phenomenon sensor systems for maritime monitoring, that is capable of surveying and monitoring rivers, ports, bays, coastal regions, and the high seas to conduct search operations, monitor for dangerous cargoes, prevent drug and migrant smuggling, enforce fisheries laws, monitor environmental conditions and living marine resources, inspect marine infrastructures, provide navigational aids, and to investigate marine accidents.

A method for controlling an unmanned aerial vehicle (UAV) includes receiving, by a processor of the UAV, a plurality of images captured by an imaging device coupled to the UAV, identifying, by the processor, a target in at least one image of the plurality of images, determining, by the processor, whether the target is a stationary target or a moving target based on analyzing the plurality of images, and automatically effecting, by the processor, movement of the UAV based on determining the target is the stationary target or the moving target.

A method for implementing obstacle avoidance of a movable object within an environment is provided. The method includes determining whether the movable object is going to collide with one or more obstacles based on a predicted movement of the movable object along a motion path. The motion path is incrementally adjusted in at least one direction in response to the movable object being determined to collide with the one or more obstacles. For each incremental angle in the at least one direction, whether the movable object is going to collide with the one or more obstacles is determined.

A method of obtaining and geo-registering an aerial image of an object of interest is provided. The method includes obtaining an aerial image and accessing an object detection model trained using a machine learning algorithm. The method includes training set of aerial images of an object of interest, and using the object detection model to detect the object of interest in the aerial image. The object detection includes a prediction of a boundary of the object of interest depicted in the aerial image based on the defined boundary of the object of interest. And the method includes geo-registering the aerial image including the prediction of the boundary of the object of interest with a geographic location of the object of interest.

An example system for flying to a target location is provided, comprising a parent aerial vehicle and at least one child vehicle releasably coupled to the parent vehicle. The parent vehicle is configured to transport the at least one child aerial vehicle to a region containing a target location, uncouple from the at least one child aerial vehicle, and transmit information to the at least one child aerial vehicle relevant to operation of the child aerial vehicle. The child aerial vehicle comprises at least one sensor for surveillance at the target location.

An unmanned aerial vehicle is described and includes a computer carried by the unmanned aerial vehicle to control flight of the unmanned aerial vehicle and at least one sensor. The unmanned aerial vehicle is caused to fly to a specific location within a facility, where the unmanned aerial vehicle enters a hover mode, where the unmanned aerial vehicle remains in a substantially fixed location hovering over the specific location within the facility and sends raw or processing results of sensor data from the sensor to a remote server system.

A threat response system includes a response and alert generator to, based on one or more data feeds with event type data and event location data related to a surveilled area, classify an event, determine a total score of the event compared to a predetermined threat threshold, and output one or more response operations based on the event classification and the total score of the event. A response plan database is included to store and/or predict one or more predetermined action plans operable to direct one or more unmanned aerial vehicle (UAVs) to respond to the event. An event database is included to store a project of event types predetermined as suitable for a UAV response. A controller of the system can receive data from one or more data feeds associated with the surveilled area to determine a match between event data and one or more event types in the event database.