This short book presents a research project dealing with a humanoid robot called iCub that is able to autonomously and accurately fire toy bullets at a bulls-eye target in lab conditions. Therefore, this monograph is framed within the context of mobile robots that can aid and assist soldiers on the battlefield.

From a technical point of view, this book covers the following issues: robot kinematics, computer vision, and machine learning. In particular, chapter 4 details the kinematic model of the arms of the iCub robot in terms of the Denavit-Hartenberg convention. The iCub robot is introduced in this chapter as well. Chapter 5 explains the application of the Hough circle transform for determining the location of the desired target. Machine learning is reviewed in chapter 6. The authors briefly explain how iCub can utilize its past experiences as a point of reference and predict the location of the (dynamic) target after a set time interval.

The book includes six other chapters. The first three (chapters 1 through 3) provide an introduction to the application of robots in the military, an overview of probability, and a survey of the mathematical concepts of matrices and determinants. Chapter 7 remarks on the importance of considering bullet dynamics in order to achieve a successful shot. One physical experiment (only pictures of the iCub robot) is given in chapter 8. Chapter 9 ends the book with conclusions and future research directions.

Although the authors have raised an interesting topic, I do not consider this book a valuable reference for a scientist or technician. It lacks comprehensive analysis of the physical experiments, and readers will miss comparisons with similar approaches. Furthermore, the concepts addressed in chapters 2 to 4 are thoroughly reviewed in more appropriate references [1,2,3]. In subsequent chapters, the technical contribution is pretty weak; the authors simply give a general idea and do not detail its novelties.