Springer RITA 2018: Proceedings of the 6th International Conference on Robot Intelligence Technology and Applications (Lecture Notes in Mechanical Engineering)

This book gathers the Proceedings of the 6th International Conference on Robot Intelligence Technology and Applications (RITA 2018). Reflecting the conference’s main theme, “Robotics and Machine Intelligence: Building Blocks for Industry 4.0,” it features relevant and current research investigations into various aspects of these building blocks. The areas covered include: Instrumentation and Control, Automation, Autonomous Systems, Biomechatronics and Rehabilitation Engineering, Intelligent Systems, Machine Learning, Robotics, Sensors and Actuators, and Machine Vision, as well as Signal and Image Processing. A valuable asset, the book offers researchers and practitioners a timely overview of the latest advances in robot intelligence technology and its applications.  From the Back Cover This book gathers the Proceedings of the 6th International Conference on Robot Intelligence Technology and Applications (RITA 2018). Reflecting the conference’s main theme, “Robotics and Machine Intelligence: Building Blocks for Industry 4.0,” it features relevant and current research investigations into various aspects of these building blocks. The areas covered include: Instrumentation and Control, Automation, Autonomous Systems, Biomechatronics and Rehabilitation Engineering, Intelligent Systems, Machine Learning, Robotics, Sensors and Actuators, and Machine Vision, as well as Signal and Image Processing. A valuable asset, the book offers researchers and practitioners a timely overview of the latest advances in robot intelligence technology and its applications. About the Author Dr. Anwar P.P. Abdul Majeed graduated with a first class honours B.Eng. in Mechanical Engineering from Universiti Teknologi MARA (UiTM), Malaysia. He obtained an M.Sc. in Nuclear Engineering from Imperial College London, United Kingdom. He then received his Ph.D. in Rehabilitation Robotics under the supervision of Prof. Dr. Zahari Taha from Universiti Malaysia Pahang (UMP). He is currently serving as a senior lecturer at the Faculty of Manufacturing Engineering, UMP. He is an active research member at the Innovative Manufacturing, Mechatronics and Sports Laboratory, UMP. His research interest includes computational mechanics, applied mechanics, sports engineering, renewable and nuclear energy, sports performance analysis as well as machine learning.  Mr. Jessnor Arif Mat Jizat graduated as Diplomingenieur (FH) in Mechatronics Engineering from Hochschule Karlsruhe Technik and Wirtschaft, Germany. He obtained a M.Eng.(Manufacturing) by research in Automated Guided Vehicle using computer vision from Universiti Malaysia Pahang. He is currently pursuing his Ph.D. studies at the Innovative Manufacturing, Mechatronics and Sports Laboratory, Faculty of Manufacturing Engineering, Universiti Malaysia Pahang under the supervision of Professor Zahari Taha. His research interest includes robotics vision, sports engineering, autonomous vehicle.  Dr. Mohd Hasnun Arif Hassan earned his first degree in Mechanical Engineering from the Technische Hochschule Bingen in Germany in 2010. He then pursued a Master’s degree in Mechanical Engineering at the University of Malaya in Kuala Lumpur, graduating with distinction in 2012. After that, he embarked on his Ph.D. at the Universiti Malaysia Pahang (UMP), where he studied the head injuries sustained by soccer players due to heading. He completed his Ph.D. study in 2016, then continued to serve UMP as a senior lecturer. He is currently the director of the Innovative Manufacturing, Mechatronics and Sports Laboratory (iMAMS), which was founded by Professor Zahari Taha, who was his supervisor for his doctoral study. His research interests include finite element modelling of the interaction between human and sports equipment, instrumentation of sports equipment, and injury prevention particularly with regard to sport. His work aims to apply engineering principles in sports to not only enhance the p