Autonomous navigation system for a rover with robotic arm using convolutional neural networks

Abstract

The aim of this project is to design and develop an autonomous rover equipped with a KUKA robotic arm. This mobile vehicle will be able to move autonomously thanks to the use of machine learning techniques. It will also be able to detect and retrieve objects using the KUKA arm. The rover will feature Mecanum wheels for improved maneuverability and will be controlled by a Raspberry Pi 3 board, with machine learning algorithms implemented using TensorFlow and Python. The development process will follow the V-methodology. The use of such an autonomous rover and its manipulative capabilities opens the way to many practical applications, including sampling in dangerous or difficult-to-access environments, search and rescue operations in the event of natural disasters or industrial accidents, and inspection and maintenance of industrial or construction sites. The rover could also be used for educational purposes, enabling students to explore the concepts of robotics and artificial intelligence.