The Proceedings of Mechanical Engineering Congress, Japan
Online ISSN : 2424-2667
ISSN-L : 2424-2667
2022
Session ID : F182-02
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Developing Drone AI to Avoid Risks Using Deep Learning
*Kenji IWATA
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Abstract

To improve the reliability and safety of autonomous drone navigation, we are conducting research and development with the aim of realizing "no-fall/safe-to-fall" drones equipped with deep learning AI technology. It consists of autonomous operation AI technology that detects people and vehicles and avoids flying over them, failure diagnosis AI technology that detects malfunctions and unstable behavior based on onboard drone sensors and telemetry information, and emergency landing AI technology that moves to a safe area and lands when a failure is diagnosed. Techniques for finding a safe area for a drone to land during an emergency landing and approaches to ensure object detection performance are described.

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© 2022 The Japan Society of Mechanical Engineers
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