Patent classifications
G08G5/0026
Pre-emptive generation of autonomous unmanned aerial vehicle inspections according to monitored sensor events
Methods, systems and apparatus, including computer programs encoded on computer storage media for generation of autonomous unmanned aerial vehicle flight plans based on triggered sensor information. One of the methods includes accessing information correlated from sensors monitoring features of weather events, and determining an upcoming weather event, the determination comprising one or more areas expected to be affected by the weather event. A likelihood of damage associated with the weather event is determined to be greater than a threshold in the areas. The weather event is monitored while areas in which the likelihood is greater than the threshold are updated accordingly. Subsequent to the weather event, properties to be inspected by unmanned aerial vehicles are determined based on severity information associated with the weather event. Job information is generated, the job information being associated with inspecting the determined properties, the job information including jobs each assignable to operators for implementation.
LOCAL ELECTRONIC ENVIRONMENTAL DETECTION DEVICE
The present invention relates to a method and system for gathering data along points of travel using common portable electronic devices that are typically used for other functions. More specifically, the data gathered by these portable electronic devices may be accessed, processed, validated, and used in conjunction with, or alone, to produce, augment, and/or validate other data sets across wide ranges of science and technology.
DEVICE AND METHOD FOR AUTOMATIC PROPOSAL OF AIR-CONFLICT RESOLUTION
A method for automatically proposing an air conflict resolution, the method includes a step of receiving air conflict and air situation data at a time when an air conflict is detected, the method comprising the steps of: determining a conflict category associated with the detected air conflict based on the conflict data; determining a degree of relevance in proposing a resolution to the air conflict according to the category and the air situation; determining one or more types of resolution to be applied to resolve the detected air conflict according to the degree of relevance; determining set of alternative trajectories corresponding to the one or more types of resolution; determining a set of candidate trajectories from among the set of alternative trajectories, a candidate trajectory being an alternative trajectory which does not generate an air conflict; selecting, from among the candidate trajectories, a candidate trajectory which fulfills a selection criterion relating to the operational relevance of the candidate trajectories and to the acceptability of the candidate trajectories by the flight plan management system; returning the candidate trajectory, the candidate trajectory being saved and re-evaluated as long as it does not generate an air conflict or has not been accepted by an air traffic controller.
Multiple unmanned aerial vehicles navigation optimization method and multiple unmanned aerial vehicles system using the same
According to a technical aspect of the invention, there is provided a multiple unmanned aerial vehicles navigation optimization method is performed at a ground base station which operates in conjunction with unmanned aerial vehicles-base stations which are driven by a battery to move and cover a given trajectory point set, the multiple unmanned aerial vehicles navigation optimization method including: calculating an age-of-information metric by receiving an information update from the unmanned aerial vehicles-base stations through communication, when the ground base station is present within a transmission range of the unmanned aerial vehicles-base stations; setting conditions of a trajectory, energy efficiency, and age of information of each of the unmanned aerial vehicles-base stations; and executing Q-learning for finding a trajectory path policy of each of the unmanned aerial vehicles-base stations, so as to maximize total energy efficiency of an unmanned aerial vehicles-base station relay network to which the energy efficiency and the age of information are applied. According to the invention, the following effects are obtained. Age of information (AoI) that is a new matrix used to measure up-do-dateness of data is set, an edge computing environment for a remote cloud environment is provided by using the AoI, and a computing-oriented communications application can be executed by using the edge computing environment.
System and method for optimizing mission fulfillment by unmanned aircraft systems (UAS) via dynamic atmospheric modeling
A system and method for optimizing mission fulfillment via unmanned aircraft systems (UAS) within a mission space generates or receives atmospheric models forecasting weather and wind through the mission space, the atmospheric models having an uncertainty factor. Until the projected flight time, the controller may iterate through one or more simulations of a projected flight plan through the mission space, determining the probability of successful fulfillment of mission objectives based on the most current atmospheric models (including the ability of the UAS to navigate the flight plan within authorized airspace constraints). Based on conditions and behaviors observed during a simulated flight plan, the controller may revise flight plans, flight times, or atmospheric models for subsequent simulations. Based on multiple probabilities of fulfillment across multiple simulations, the controller selects an optimal flight plan and/or flight time for fulfillment of the assigned set of mission objectives.
FLIGHT DATA AGGREGATION SYSTEM INCLUDING PORTABLE ELECTRONIC DEVICES
A flight data aggregation system for a plurality of aircraft includes one or more portable electronic devices in electronic communication with one or more central computers. The one or more portable electronic devices each monitor flight data from a corresponding aircraft. The one or more portable electronic devices analyze the flight data in real-time to determine an insight event indicating an incident of significance is presently occurring upon the corresponding aircraft. Each central computer includes one or more processors and a memory coupled to the one or more processors. The central computers are caused to receive the flight data collected during the insight event from an individual portable electronic device. The central computers determine overall flight data patterns based on the flight data collected during the insight event received from the individual portable electronic device and historical data stored in the one or more databases.
INCENTIVIZING UNMANNED AERIAL VEHICLE USE
Methods, systems, apparatuses, and computer program products for incentivizing UAV use are disclosed. In a particular embodiment, incentivizing UAV use includes UAV pilot recommendation by a computing system. In this embodiment, the computing system receives at least one parameter related to a prospective UAV mission and retrieves UAV flight records of a plurality of UAV pilots. According to this embodiment, the computing system recommends, based on the at least one parameter and the UAV flight records, at least one UAV pilot for the prospective UAV flight.
SELECTION OF UNMANNED AERIAL VEHICLES FOR CARRYING ITEMS TO TARGET LOCATIONS
In various aspects, a first set of attributes associated with a target location are determined. The target location is a location that one or more items are to be delivered to by an unmanned aerial vehicle (UAV). The first set of attributes are compared with a second set of attributes. The second set of attributes indicate attributes of each UAV of a plurality of UAVs. Based on the comparing, a UAV, of the plurality of UAVs, is recommended to deliver the one or more items to the target location.
GENERATING AND DISTRIBUTING GNSS RISK ANALYSIS DATA FOR FACILITATING SAFE ROUTING OF AUTONOMOUS DRONES
Disclosed is route planning using a worst-case risk analysis and, if needed, a best-case risk analysis of GNSS coverage. The worst-case risk analysis identifies cuboids or 2d regions through which a vehicle can be routed with assurance that adequate GNSS coverage will be available regardless of the time of day that the vehicle travels. The best-case risk analysis identifies cuboids or 2d regions through which there is adequate coverage at some times during the day. In case path finding using the worst-case risk analysis fails, a best-case risk analysis can be requested and used to find alternate potential path(s). Time dependent forecast data that covers regions along the alternate potential path(s) can be requested and used to route vehicles, including autonomous drones, from starting points to destinations. This includes generation, distribution and use of risk analysis data, implemented as methods, systems and articles of manufacture.
Drone Air Traffic Control Over Satellite Networks
An Unmanned Aerial Vehicle (UAV) air traffic control method utilizing wireless networks includes communicating with a plurality of UAVs via a plurality of satellites associated with the wireless networks, wherein the plurality of UAVs each include hardware and antennas adapted to communicate to the plurality of satellites; maintaining data associated with flight of each of the plurality of UAVs based on the communicating; and processing the maintained data to perform a plurality of function associated with air traffic control of the plurality of UAVs.