Unmanned Aerial Vehicles or UAVs are an amazing piece of machinery that have proven their usefulness in various industries like construction, military, logistics, filmmaking, etc. They’re either operated remotely by a human controller from the ground or have automated capabilities to control its own flight. But due to several technological and environmental restrictions there are many models that can guarantee complete autonomous behavior of the drone. For being truly autonomous, UAVs will need to get far better at sensing its surroundings and obstacles to decide its own path and react in time to avoid collisions. This project specifically aims at enhancing the drones used in the tourism sector for the betterment of traveling experience of people by automating the process of capturing their experience along with autonomous flight capabilities. ML enabled cinematography drones to tackle the gap in the market where good camera drones are unavailable at a lower price point with an added benefit of hands-free automated flight patterns to capture cinematic shots. We have tried to achieve this milestone by using sensors that can detect the surrounding obstacles in real-time and manipulate its flight path to capture cinematic shots of the target object. Through the project we’re also automating various shots like hover, 360 degree view, follow at focus,etc that the drone will include into its flight path on the go. Operating an unmanned flying machine is very challenging especially when you’re flying the drone out of your line of sight and detecting objects using just one FPV camera or monitoring several cameras at the same time is not humanly possible. Hence, through this project we’re not only allowing travellers to enjoy their journey but also take videos of places they can’t reach without having to worry about losing or crashing their drones. There can be further research on this flying model to inculcate it for various industries as the flying pattern and requirement changes in each sector.
Cinematography Drone with Automated Ability for Self-flight and Maneuverability: A Review
2022-03-27
oai:zenodo.org:6387632
Article (Journal)
Electronic Resource
English
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