The robot intelligence aspect of aerial robots is the core part that allows a robot to reason about the environment and its current status in order to accomplish a required mission. This book offers researchers and PhD students involved in unmanned aerial systems a comprehensive theoretical survey of aerial robot intelligence. In particular, it is focused on motion planning and decision making. Motion planning concentrates on obtaining a continuous route from one starting point to a desired target and following the route as closely as possible by means of control actions. In general, between these two points there is a sequence of waypoints that define the mission of the robot. This level is related to decision making (discrete actions). The efficiency and safety of aerial robot movement depend on how motion planning and decision making are combined.

The book moves from simple approaches (motion planning and deterministic decision making for one single robot) to more complex methods (decision making under uncertainty and multi-robot systems). The context and motivation of the book are introduced in chapter 1. The hierarchical control architectures dealing with one single robot and a multi-robot system are also explained. This chapter reviews several fundamental topics for the coming chapters: probability, uncertainty, nonlinear control, graph theory, and linear temporal logic. This first chapter is followed by a comprehensive survey of motion planning algorithms in aerial robotics. In particular, some well-known approaches dealing with path planning are explained. Obstacle avoidance and motion control are introduced as well. The next chapter addresses the decision making aspect. Here, some approaches that are able to deal with hybrid information are detailed (symbolic planning methods). Regarding the aspect of intelligent decision making, a set of artificial intelligence (AI)-based approaches are reviewed (such as neural networks, evolutionary algorithms, and fuzzy logic). Arc routing methods are also included in order to schedule aerial missions. This chapter closes with some simulations.

Chapter 4 deals with a fundamental concern in real applications: uncertainty. This concern leads to replacing deterministic approaches with Bayesian inference, stochastic solutions, or Markov-based methods. Several case studies show the applicability of these techniques. Chapter 5 addresses the specific topic of cooperation in a multi-robot system. In this sense, the general motion planning and decision making approaches presented until now must be reformulated. Four case studies show the application of these new techniques. The volume closes with a short one-page chapter with conclusions and future research.

I do not consider this book a valuable reference for introductory and practical courses because it lacks physical experiments and it excludes basic concepts such as sensory systems, actuators, modeling, and programming issues, among others.