This book addresses the challenging problem of employing aerial robots to transport and manipulate loads safely and efficiently, discussing in detail the design and derivation of control algorithms based on adaptive control, optimal control, and reinforcement learning.

Unmanned aerial vehicles are increasingly being used to perform complex functions or to assist humans in dangerous missions in dynamic environments. Other possible applications include search and rescue, disaster relief operations, environmental monitoring, wireless surveillance networks, and cooperative manipulation. Creating these autonomous aerial vehicles presents significant challenges in terms of designing control schemes that can adapt to different scenarios and possible changes in vehicle dynamics. Further, aerial load manipulation and transportation is extremely important in emergency rescue missions, as well as military and industrial applications.

This book provides insights into the problems that can arise in aerial load transportation and suggests control systems techniques to address them. It particularly focuses on modeling the aerial load transportation system, as well as stability and robustness analysis. It also describes an experimental testbed and controller implementation.