Bilby Rover autonomous mobile robot in the context of Industry 4.0 - Survey on sensor-enabled applications through Webots simulations and implementation of Hector-SLAM algorithm for autonomous navigation

In the light of Industry 4.0 revolution, the advances in information technology like Internet of Things, Artificial Intelligence, Cloud Computing, Cyber-Physical Systems and Big Data are changing the use and design of robots in the industry. Robotics, which is a multidisciplinary field that builds on the intersection of mechanical and electrical engineering, computer science, communication and networking, and material technology, is undergoing dramatic developments in recent years, as the landscape of Industry 4.0 is progressively unfolding. This thesis stems from the collaboration with McMaster’s W Booth School of Engineering Practice and Technology and aims at studying and simulating a model of an autonomous mobile robot, called Bilby Rover. The first section of the project provides a review of literature and research related to Industry 4.0, outlining its enabling technologies, future opportunities and implications in the field of robotics. The mobile autonomous robot Bilby Rover is then presented in the second part, where the mechatronic description and the kinematic model of the system are provided. Additionally, the concept of Simultaneous Localization and Mapping (SLAM) is introduced, proposing a summary of the state of the art of the most widely used technologies. The third section is aimed at exploring through virtual simulations a set of potential industrial applications of the Bilby Rover, enabled by the integrated deployment of specific sensors: for this purpose, Webots robotic simulator is exploited. In the view of transferring this technology into the physical robot, the last section of the thesis is dedicated to a literature review concerning the Hector-SLAM algorithm for Simultaneous Localization and Mapping. Thereafter, the algorithm is tested using the Raspberry Pi single-board computer and the YDLIDAR X4 Lidar sensor, which, for this purpose, are appropriately integrated into the open-source Robot Operating System (ROS) framework.