Drones and Autonomous Robotics Incorporating Computational Intelligence

Abstract

Computational intelligence (CI) has emerged as a powerful paradigm in the field of autonomous robotics and drones, enabling the development of intelligent, adaptive, and self- learning systems. This chapter explores the application of CI techniques in autonomous robotics and drones, focusing on the utilization of artificial intelligence, machine learning, and swarm intelligence algorithms to enhance navigation, perception, decision-making, and collaboration capabilities. The journey starts with an introduction to autonomous robotics and drones, outlining the challenges and opportunities in developing self-sufficient systems. It then delves into the fundamentals of CI, explaining the concepts of artificial intelligence, machine learning, and swarm intelligence, and their significance in autonomous systems. The core aspects of autonomous robotics and drones are addressed, including navigation and path planning, object detection and recognition, and adaptive control. It highlights the use of CI algorithms for intelligent decision-making, real-time object detection using deep learning, and cooperative navigation with swarm robotics. Furthermore, the abstract explores the emerging field of autonomous drone delivery systems, discussing the challenges and regulatory considerations involved in implementing efficient and safe drone delivery services. Human–robot interaction and collaboration play a pivotal role in autonomous systems, and the abstract discusses how CI techniques facilitate natural language processing for seamless communication and the development of empathetic robots. The future trends and challenges in the field are also examined, such as AI at the edge, ethical implications, and the gap between research and real-world deployment. It emphasizes the transformative impact of CI in autonomous robotics and drones. By harnessing the power of AI, machine learning, and swarm intelligence, these intelligent systems are poised to revolutionize various industries and contribute to a more automated and efficient future. However, it also highlights the need for addressing ethical considerations and ensuring responsible deployment for the widespread acceptance and success of autonomous systems in the real world.