There has been a growing global trend towards convenience, speed, and ease in delivery services, and this has been further accelerated by the COVID pandemic. With the everincreasing demand for easily accessible deliveries and expanded delivery service coverage, it has become critical that innovations in this space be developed to further ensure the industry’s smooth operation. With the emergence of the COVID-19 pandemic, the inadequacies became more apparent, emphasizing the need to revolutionize and accelerate the trend in order to meet the increased demand. Drone delivery systems are of particular interest in this context because they can enable faster and more cost-effective delivery. This paper introduces a navigation system that simplifies the delivery of food parcels with independent drones. The system generates a path between the start and endpoints and controls the drone to follow this path based on its location obtained by planning the route through various sensors like LiDAR. The drone also avoids obstacles that come its way to achieve the intended goal, hence autonomously navigating its path. In the landing phase, marker information (ArUco Tag) uses a camera, and the drone software scale is integrated using an expanded Kalman filter algorithm to improve landing accuracy. The vector-based approach controls the drone to fly the desired path smoothly, minimizing vibrations or strong movements that could damage the transported package.
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Patel, Hrishitva, "Designing autonomous drone for food delivery in Gazebo/Ros based environments" (2022). Computer Science and Engineering Research. 6.