Sierra Nevada has been granted a patent for a system that deploys airbags or bladders to reduce the impact and provide buoyancy in the event of a failure or collision of a UAV. The system includes modules for communication, battery, GPS, and sensors, and is capable of initiating controlled descent and inflating the bladders based on identified threats. It also transmits a distress signal with relevant information. GlobalData’s report on Sierra Nevada gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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According to GlobalData’s company profile on Sierra Nevada, IoT network security was a key innovation area identified from patents. Sierra Nevada's grant share as of September 2023 was 55%. Grant share is based on the ratio of number of grants to total number of patents.
Patent granted for a uav buoyancy and impact recovery system
A recently granted patent (Publication Number: US11753161B2) describes a buoyancy and impact recovery system for unmanned aerial vehicles (UAVs). The system includes various components such as a communication module, battery module, global positioning module (GPS), sensor modules, controlled descent module, and inflatable bladders. The inflatable bladders are stored in an uninflated arrangement and can be inflated based on identified threats to the UAV.
The system is designed to receive sensor data from one or more sensors and use this data to identify threats to the UAV. Based on the identified threats and sensor data, the system initiates mitigation procedures, including a controlled descent process to reduce the rate of descent and an impact reduction process that involves inflating the inflatable bladders. Additionally, the system can transmit a distress signal through the communication module, providing information about the incident type, UAV position during the controlled descent process, current UAV position, and the status of the UAV and system.
The controlled descent module in the system can be implemented using a parachute or by controlling the rotors to establish an autorotation descent. The threats to the UAV can be determined to be structures or malfunctions/failures of the rotors. To identify threats, the system aggregates sensor data, analyzes it using machine learning models, classifies possible threats, determines threat levels, and tracks the threats when their threat level exceeds a predetermined threshold. The aggregated data can include image data from camera sensors, and computer vision models can be used to identify visual threats and maintain a record of their position, orientation, and distance. Inertial measurement unit data can also be used, and machine learning models can predict component health and determine threat levels for component failure threats by predicting the time to failure for critical components.
Overall, this patent describes a comprehensive system for buoyancy and impact recovery in UAVs, utilizing sensor data, machine learning models, and various modules to identify threats, initiate mitigation procedures, and transmit distress signals. The system's ability to control descent and inflate bladders provides a potential solution for reducing the impact of threats and improving the safety of UAV operations.
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GlobalData Patent Analytics tracks bibliographic data, legal events data, point in time patent ownerships, and backward and forward citations from global patenting offices. Textual analysis and official patent classifications are used to group patents into key thematic areas and link them to specific companies across the world’s largest industries.
