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—The presented paper describes the design and implementation process of a six-wheeled autonomous robotic platform. The device is equipped with advanced object recognition algorithms based on neural networks. It is low cost and easy to build a device capable of roving in varied terrain. It is ideal for scouting missions, or mapping visited areas. Following a brief introduction into the explored topic, a design process of a considered robot. Mechanical, electronic and onboard sensory systems are found in the next part of the article. The following section consists of a description of the control and navigation approach used in our system. Then, YOLO object recognition algorithm is explained, followed by a proposed experiment to validate its abilities. Set of tasks were given to the robot, that had to complete them autonomously. Results are highly satisfying. The YOLO algorithm proved useful in object recognition providing crucial data required during autonomous drive mode.
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