Abstract

Unmanned aerial vehicles are the cutting edge technology which is used in various arduous applications and emergency scenarios. But human operators find it burdensome and experience a lot of physical and mental stress while operating the aerial systems in critical and emergency scenarios such as rescue operations, mine inspection, and surveillance. Our proposed idea is to provide the autonomous capability and features to these automatons by developing a mission-planning application that can autonomously guide UAV operations even in GPS denied environments by implementing SLAM (Simultaneous Localization and Mapping). With autonomous capability, aerial systems can help to plummet the stress on human operators or may even perform the process or mission efficiently without human intervention in numerous applications. Applications involving autonomous unmanned aerial systems have increased in recent times and are being applied in a wide range of fields such as infrastructure, transport, agriculture, mining, media, and transport. This paper covers the working of the autonomous navigation algorithm, artificially intelligent object detection algorithm and the mission planning API (Application Programming Interface).

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