Extending drone’s capabilities for autonomous flight approach combined with indoor pod delivery mechanism

Abstract

Drone technology is being tested and used in various fields today. Using drones to deliver items is one of the most promising aspects of the technology which is being developed by many companies around the world. It is very challenging to develop algorithms to decide flight paths and maneuver drones autonomously in the real world. Making an autonomous flying vehicle requires interdisciplinary approach. An array of various sensors working together and sharing data combined with machine learning models to analyze and act on that data is paramount for executing the level of autonomy required to achieve this feat. The drone needs to have intuitive understanding of routes. Removing discrepancies in the flight path requires well-constructed algorithms to assess the real life situations and make decisions to tackle problems which might occur due to accidents, collisions, onboard control issues etc. The technology should be optimal enough to handle practical constraints such as battery life, distance of travel, weather proofing etc. This paper focuses on the tools and algorithms available today and how they can be extended and modified to make a delivery system by combining delivery drones and a network of indoor tubes to deliver the item directly to one’s home without them having to collect it outside.