A system for aerial neutralization of a detected target aerial vehicle comprises a plurality of counter-attack unmanned aerial vehicles (UAVs), and an aerial vehicle capture countermeasure coupling together the plurality of counter-attack UAVs, to intercept and capture a detected target aerial vehicle in a coordinated manner. The system comprises an aerial vehicle detection system comprising at least one detection sensor operable to detect the target aerial vehicle, and operable to provide command data to at least one counter-attack UAV for tracking and neutralizing the target aerial vehicle. The counter-attack UAVs and a net can be deployed from a movable base station, and the net can be carried in a low-drag configuration until the counter-attack UAVs operate to deploy or open the net. The counter-attack UAVs and systems may be autonomously operated. Associated systems and methods are provided.

An automated structural feature and analysis system is disclosed. A 3D device emits a volume scanning 3D beam that scans a structure to generate 3D data that is associated with a distance between the 3D device and each end point of the 3D beam positioned on the structure. An imaging device captures an image of the structure to generate image data with the structure as depicted by the image of the structure. A controller fuses the 3D data of the structure generated by the 3D device with the image data of the structure generated by the imaging device to determine the distance between the 3D device and each end point of the 3D beam positioned on the structure and to determine a distance between each point on the image. The controller generates a sketch image of the structure that is displayed to the user.

Disclosed here are methods and systems for automatically operating automated vehicles moving through vegetation obstacles with minimal damage, comprising receiving image(s) depicting vegetation obstacle(s) blocking at least partially a path of an automated vehicle executing a mission, analyzing the image(s) to extract one or more obstacle attributes of the vegetation obstacle(s), computing a plurality of movement patterns for operating the automated to cross the vegetation obstacle(s) based on one or more vehicle attributes of the automated vehicle with respect to one or more of the obstacle attributes where each movement pattern defines one or more movement parameters of the automated vehicle, selecting one of the movement patterns estimated to reduce a cost of damage to the automated vehicle and/or to the one or more vegetation obstacles, and outputting instructions for operating the automated vehicle to move through the vegetation obstacle(s) according to the selected movement pattern.

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for an unmanned aerial system inspection system. One of the methods is performed by a UAV and includes obtaining, from a user device, flight operation information describing an inspection of a vertical structure to be performed, the flight operation information including locations of one or more safe locations for vertical inspection. A location of the UAV is determined to correspond to a first safe location for vertical inspection. A first inspection of the structure is performed is performed at the first safe location, the first inspection including activating cameras. A second safe location is traveled to, and a second inspection of the structure is performed. Information associated with the inspection is provided to the user device.

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for an unmanned aerial system inspection system. One of the methods is performed by a UAV and includes obtaining, from a user device, flight operation information describing an inspection of a vertical structure to be performed, the flight operation information including locations of one or more safe locations for vertical inspection. A location of the UAV is determined to correspond to a first safe location for vertical inspection. A first inspection of the structure is performed is performed at the first safe location, the first inspection including activating cameras. A second safe location is traveled to, and a second inspection of the structure is performed. Information associated with the inspection is provided to the user device.

Overall efficiency and/or flight time of UAVs and Drones can be increased by adding elements containing lighter-than-air gasses; and/or by reducing and/or eliminating the power supplied to any combination of the motors to reduce overall power consumption. In an aspect the configuration of a blimp drone include at least one air cavity/chamber/container filled with lighter-than-air gasses. The 3D chambers are made from swept or extruded closed 2D geometry and are detachable from the Drone and can be transparent or camouflaged in color. To maintain control and altitude of the aircraft, lifting surfaces can be incorporated. Such lifting surfaces may include active and/or passive control surfaces to maintain flight stability. Additionally, cavities, fissures, orifices and valves may be added to the surface of the flying vehicle to gain other efficiency advantages.

A modular aerial vehicle for inspection of enclosed and open space environments. The aerial vehicle is employed for inspection of various environments in remotely controlled and autonomous fashions. The aerial vehicle is capable of carrying different sensory modules depending on the specific application including surface inspection. Aerial vehicle may be connected to a tether cable for electrical power delivery and transmission of control commands. The aerial vehicle may utilize a landing structure which allows landing on any angled metallic or non-metallic surface.

Methods and apparatus are provided for allocating tasks to be performed by one or more autonomous vehicles to achieve a mission objective. Generally, a task allocation system identifies a final task associated with a given mission objective, identifies predecessor tasks necessary to complete the final task, generates one or more candidate tasks sequences to accomplish the mission objective, generates a task allocation tree based on the candidate task sequences, and searches the task allocation tree to find a task allocation plan that meets a predetermined selection criteria (e.g., lowest cost). Based on the task allocation plan, the task allocation system determines a task execution plan and generates control data for controlling one or more autonomous vehicles to complete the task execution plan.

An approach is provided for dynamic obstacle data in a collision probability map. The approach, for example, involves monitoring a flight of an aerial vehicle through a three-dimensional (3D) space that is partitioned into 3D shapes of varying resolutions. The approach also involves detecting an entry of the aerial vehicle into one 3D shape of the plurality of 3D shapes. The approach further involves, on detecting an exit of the aerial vehicle form the one 3D shape, recording a 3D shape identifier (ID) of the one 3D shape and at least one of a first timestamp indicating the entry, a second timestamp indicating the exit, a duration of stay in the one 3D shape, dimensions of the aerial vehicle, or a combination thereof as a dynamic obstacle observation record. The approach further involves transmitting the dynamic obstacle observation record to another device (e.g., a server for creating the collision probability map).

A method and system of measuring a radio wave distribution of a radio signal source and estimating corresponding radio characteristics by using a flying vehicle is provided. The method includes the following steps. At a number of flight positions during a measurement process, a number of first radio signals transmitted by the radio signal source are measured by the flying vehicle. A position of the radio signal source is estimated according to the first radio signals and a radio channel model. A number of first radio characteristics of the first radio signal are obtained, and a radio wave distribution of the radio signal source is estimated according to the first radio characteristics of the first radio signals and a number of second radio characteristics of a number of second radio signals in the radio wave distribution are estimated according to the first radio characteristics of the first radio signals.