Artificial Intelligence for Robotics and Autonomous Systems Applications

This book addresses many applications of artificial intelligence in robotics, namely AI using visual and motional input. Robotic technology has made significant contributions to daily living, industrial uses, and medicinal applications. Machine learning, in particular, is critical for intelligent robots or unmanned/autonomous systems such as UAVs, UGVs, UUVs, cooperative robots, and so on. Humans are distinguished from animals by capacities such as receiving visual information, adjusting to uncertain circumstances, and making decisions to take action in a complex system. Significant progress has been made in robotics toward human-like intelligence; yet, there are still numerous unresolved issues. Deep learning, reinforcement learning, real-time learning, swarm intelligence, and other developing approaches such as tiny-ML have been developed in recent decades and used in robotics.

Artificial intelligence is being integrated into robots in order to develop advanced robotics capable of performing multiple tasks and learning new things with a better perception of the environment, allowing robots to perform critical tasks with human-like vision to detect or recognize various objects. Intelligent robots have been successfully constructed using machine learning and deep learning AI technology. Robotics performance is improving as higher quality, and more precise machine learning processes are used to train computer vision models to recognize different things and carry out operations correctly with the desired outcome.

We believe that the increasing demands and challenges offered by real-world robotic applications encourage academic research in both artificial intelligence and robotics. The goal of this book is to bring together scientists, specialists, and engineers from around the world to present and share their most recent research findings and new ideas on artificial intelligence in robotics.

Presents recent research in Artificial Intelligence for Robotics and Autonomous Vehicle Applications Covers practical applications of remote sensing using robotics and AI Shows new applications of robotics and AI together with advances in machine learning techniques for image analysis

Autorentext
Prof. Ahmad Azar is a research professor at Prince Sultan University, Riyadh, Kingdom Saudi Arabia, and an associate director of research and initiative center. He is a lab leader of Automated Systems & Soft Computing Lab (ASSCL) at Prince Sultan University, Riyadh, Saudi Arabia. He is also a professor at the Faculty of Computers and Artificial Intelligence, Benha University, Egypt. He is currently an associate editor for IEEE Systems Journal, IEEE Transactions on Neural Networks and Learning Systems, Springer's Human-centric Computing and Information Sciences, and Elsevier's Engineering Applications of Artificial Intelligence. Prof. Azar has expertise in control theory and applications, robotics, process control, artificial intelligence, machine learning, and dynamic system modeling.

Prof. Azar has received various awards, including the Benha University Prize for Scientific Excellence (2015, 2016, 2017, and 2018) and the Benha University Highest Citation Award (2015, 2016, 2017, and 2018). In June 2018, Prof. Azar received the Egyptian State Encouragement Award in Engineering Sciences from the Ministry of Higher Education and Scientific Research. In August of 2018, he was chosen as a senior member of the International Rough Set Society (IRSS). Prof. Azar was named one of the top computer scientists in Saudi Arabia by Guide2Research in December 2019. Prof. Azar received the Egyptian President's Distinguished Egyptian Order of the First Class in February 2020. In October 2020, Prof. Azar was awarded Abdul Hameed Shoman Arab Researchers Award in machine learning and big data analytics. In October 2020 and October 2021, Prof. Azar was selected as a distinguished researcher at Prince Sultan University, Riyadh, Saudi Arabia. In November 2020, October 2021, and October 2022, Prof. Azar was named one of the top 2% of scientists in the world in artificial intelligence by Stanford University. Stanford University published these numbers in the PLOS journal and based them on the SCOPUS database.

**Prof. Anis Koubaa **is a professor in Computer Science, advisor to the Rector, and leader of the Robotics and Internet of Things Research Lab in Prince Sultan University. He is also a R&D consultant at Gaitech Robotics in China and a senior researcher in CISTER/INESC TEC and ISEP-IPP, Porto, Portugal. He has been the chair of the ACM Chapter in Saudi Arabia since 2014. He is also a senior fellow of the Higher Education Academy (HEA) in UK. He received several distinctions and awards including the Rector Research Award in 2010 at Al-Imam Mohamed Bin Saud University and the Rector Teaching Award in 2016 at Prince Sultan University. He is the editor in chief of the Robotics Software Engineering topic of the International Journal of Advanced Robotics Systems and an associate editor in the Cyber-Physical Journal (Taylor & Francis). 

Inhalt
Efficient Machine Learning of Mobile Robotic Systems based on Convolutional Neural Networks.- UAV Path Planning Based on Deep Reinforcement Learning.- Drone Shadow Cloud: A New Concept to Protect Individuals from Danger Sun Exposure in GCC Countries.- Accurate Estimation of 3D-Repetitive-Trajectories using Kalman Filter, Machine Learning and Curve-Fitting Method for High-speed Target Interception.- Robotics and Artificial Intelligence in the Nuclear Industry: from Tele-operation to Cyber-physical Systems.- Deep Learning and Robotics, Surgical Robot Applications.- Deep Reinforcement Learning for Autonomous Mobile Robot Navigation.- Event Vision for Autonomous Off-road Navigation.- Multi-armed Bandit Approach for Task Scheduling of a Fixed-Base Robot in the Warehouse.- Machine Learning and Deep Learning for Robotics Applications.- A Review on Deep Learning on UAV Monitoring Systems for Agricultural Applications.- Navigation and Path Planning Techniques for UAV Swarm.- Intelligent ControlSystem for Hybrid Electric Vehicle with Autonomous Charging.- Advanced Sensor Systems for Robotics and Autonomous Vehicles.- Four Wheeled Humanoid Second-Order Cascade Control of Holonomic Trajectories. <p