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Preface

Mobile robotics comprises a successful field in the world today. It is not strange to see little mobile robots cleaning our house, or big robots moving goods in factories, harbors or airports, or even adventurous mobile robots exploring other worlds.

One common issue to all those robots deals with the problem of generating feasible paths or routes between a given starting position and a goal or target position while avoiding (static) obstacles. This problem is addressed within the area of path planning. Due to the importance of this problem in robot navigation, path planning has received considerable attention and numerous strategies have been proposed.

When a group of robots work within the same environment and cooperate in order to accomplish a high‐level task given as a high‐level specification, standard path planning algorithms employed by the robotics community, based on potential functions or road maps, may lead to wrong or even unfeasible results.

This book formulates the problem of path planning of cooperative mobile robots by using the paradigm of discrete‐event systems. First, a high‐level specification is expressed in terms of a Boolean or Linear Temporal Logic (LTL). The environment is then divided into discrete regions of a chosen geometrical shape by using cell decomposition. This book compares the performance of several cell decomposition algorithms in terms of several metrics. This decomposition can be used to define a discrete event system (DES) modeling the movement capabilities of the robot or of the team by using Transition System or Petri Net models. The obtained DES is next combined with the model of the high‐level specification to be accomplished by the group of robots. Finally, the resulting model is used to compute the trajectories via a graph search algorithm or solving optimization problems.

This book contributes an interactive software tool that the intended user can exploit in order to simulate and test all the strategies introduced and formulated in the book. This software tool, called RMTool (Robot Motion Toolbox), is freely available online and can be run in Matlab. It can be used for teaching mobile robotics in introductory courses, as the user can interact with the tool by using a Graphical User Interface (GUI), without requiring previous knowledge of Matlab.

This book is primarily aimed at undergraduate and graduate students and college and university professors in the areas of robotics, artificial intelligence, systems modeling, and autonomous control. The topics addressed in this book can also be welcomed by researchers, PhD students, and postgraduate students with a focus on robot motion planning, centralized robot planning solutions for teams of robots, and interactive teaching tools to be used in engineering courses. The contents of this book and the accompanying software tool can be employed by students and professors at the high‐school level with a previous background in mathematics and engineering.

Zaragoza, Spain

Cristian Mahulea

Iasi, Romania

Marius Kloetzer

Almeria, Spain

Ramón González