Professor of School of Engineering, Design and Built Environment, Western Sydney University, Australia. His research interests cover Industry 4.0, Additive Manufacturing, Advanced Engineering Materials and Structures (Metals and Composites), Multi-scale Modelling of Materials and Structures, Metal Forming and Metal Surface Treatment.
Abstract—This article describes the mechatronic design of a delivery octarotor drone equipped with safety features including protective bumpers for its propellers, parachute, and retractable gear. A GNSS-RTK unit provides extensive pose-refinement for trajectory tracking, while an RGBDepth Camera provides distance measurements from any present obstacles. A deep learning algorithm classifies any objects into certain categories (i.e., balloons, drones) followed by a trajectory avoidance algorithm. An onboard computer handles these sensor measurements and communicates with the autopilot for adjusting the trajectory. At the same time, it provides HD-live video feed to the base station and runs any onboard ROS-services. The resulting drone can safely land within a circular area of radius 1.5 m, while flying over, under and around obstacles or buildings. The carried payload is handled by a dual linear actuator gripper that releases it upon the drone's precise landing.
Index Terms—delivery drone, drone safety features, obstacle classification
Cite: Nikolaos Evangeliou, Nikolaos Giakoumidis, Dimitirs Chaikalis, Athanasios Tsoukalas, Halil Utku Unlu, Daitao Xing, and Anthony Tzes, "Mechatronic Design of a Delivery Octarotor Drone," International Journal of Mechanical Engineering and Robotics Research, Vol. 11, No. 5, pp. 351-356, May 2022. DOI: 10.18178/ijmerr.11.5.351-356
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