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This is the first chapter in the book Mobile Robotics: A Practical Introduction. This chapter sets the scene. It presents an introduction to the scientific issues in mobile robotics, gives an overview of the contents of each chapter, and encourages you to build your own robot to put this book into action.



   Mobile Robotics: A Practical Introduction

Mobile RoboticsAutonomous mobile robotics is a fascinating research topic, for many reasons. First, to change a mobile robot from a computer on wheels that is merely able to sense some physical properties of the environment through its sensors into an intelligent agent, able to identify features, to detect patterns and regularities, to learn from experience, to localize, build maps and to navigate requires the simultaneous application of many research disciplines. In this sense, mobile robotics reverses the trend in science towards more and more specialization, and demands lateral thinking and the combination of many disciplines.  


Engineering and computer science are core elements of mobile robotics, obviously, but when questions of intelligent behavior arise, artificial intelligence, cognitive science, psychology and philosophy offer hypotheses and answers. Analysis of system components, for example through error calculations, statistical evaluations etc. are the domain of mathematics, and regarding the analysis of whole systems physics proposes explanations, for example through chaos theory.

Second, autonomous mobile robots are the closest approximation yet of intelligent agents, the age-old dream. For centuries people have been interested in building machines that mimic living beings. From mechanical animals, using clockwork, to the software and physical agents of artificial life - the question of "what is life?" and can we understand it has always motivated research.

Perception and action are tightly coupled in living beings. To see, animals perform specific head and eye movements. To interact with the environment, they anticipate the result of their actions and predict the behavior of other objects. They alter the environment in order to communicate (so-called stigmergy) nest building in ants is an example of this.

Because of this tight coupling between perception and action there is a strong argument for investigating intelligent behavior by means of situated agents, i.e. mobile robots. In order to investigate simulations of life and lifelike agents that interact intelligently with their environment, we need to close the loop between perception and action, allowing the agent to determine what it sees. Whether we will have autonomous robots that match human intelligence within 50 years, or whether humans will even be obsolete by then (very fuzzy statements, because the definitions of "intelligent" and "obsolete" are not at all clear), as some writers predict, or whether we will have to wait another 100 years for truly intelligent household robots, as others reply, autonomous mobile robots offer a uniquely suited research platform for investigating intelligent behavior.

Third, there are commercial applications of mobile robots. Transportation, surveillance, inspection, cleaning or household robots are just some examples. However, autonomous mobile robots have not yet made much impact upon industrial and domestic applications, mainly due to the lack of robust, reliable and flexible navigation and behavior mechanisms for autonomous mobile robots operating in unmodified, semi-structured environments. Installing markers such as beacons, visual patterns or induction loops (guiding wires buried in the ground) is one way round this problem, but it is expensive, inflexible and sometimes outright impossible. The alternative navigation in unmodified environments - requires sophisticated sensor signal processing techniques which are still in their experimental evaluation phases. Case studies in this book present some of these techniques. So, to let mobile robots work in areas which are inaccessible to humans, or to perform repetitive, difficult or dangerous tasks, is yet another strong motivation for developing intelligent, autonomous robots.

And finally, there is also an aesthetic and artistic element to mobile robotics. Swarms of robots collaborating to achieve a particular task, or moving about avoiding collisions with one another and objects in their environment, beautifully designed mobile robots, like for instance micro-robots, or miniature legged robots, appeal to our sense of aesthetics. It is not surprising that mobile robots and robot arms have been used for artistic performances.

Construct Your Own Working Robot
Mobile robotics, by nature, has to be practiced. There are a range of relatively cheap mobile robots available now, which can be used for student practicals, student projects, or robotics projects at home (robotics as a hobby is rapidly gaining ground). GRASMOOR, built at the University of Manchester, is one example - it has its own on- board controller, infrared sensors, light sensors, tactile sensors, and a differential drive system'. GRASMOOR is controlled by a variant of the MIT 6270 controller, a controller with analogue and digital inputs for sensors, and pulse- width-modulated output to drive motors (the different types of sensors that can be used on robots are discussed in chapter 3, and pulse width modulation generates electric pulses of variable length to drive motors at variable speed). Like many robot micro-controllers, the 6.270 controller is based on the Motorola 6811 microprocessor.

It is not difficult to get going for a few hundred dollars, using robot kits or technical construction kits based on children's toys, some of which have micro-controllers and the necessary software environment to program the robots. A good introduction to building your own robot is Mobile Robots : Inspiration to Implementation.

If you are competent at building electronic circuits - and they needn't be very complicated - you can also use commercially available micro-controllers, and interface sensors and motors to them to build your robot. The basic message is: you don't have to invest large sums to build a mobile robot.

Experiments with Mobile Robots
This book contains 12 detailed case studies that cover the areas of robot learning, navigation and simulation. Furthermore, there are examples, exercises and pointers to open questions. One of their purposes is to indicate interesting areas of robotics research, identifying open questions and relevant problems.

A fascinating introduction to thought experiments with robots is Valentino Braitenberg's book on "synthetic psychology" (Vehicles), which contains many experiments that can be implemented and carried out on real robots.

Organization of the Book
Scientific progress rests on the successes and failures of the past, and is only achieved if the history of a scientific area is understood. This book therefore begins by looking at the history of autonomous mobile robotics research, discussing early examples and their contributions towards our understanding of the complex interaction between robots, the world they operate in, and the tasks they are trying to achieve.

A robot, obviously, is made from hardware, and the functionality of a robot's sensors and actuators influences its behavior greatly. The second chapter of the book, therefore, looks at hardware issues specifically and discusses the most common robot sensors and actuators.

A truly intelligent robot needs to be able to deal with uncertain, ambiguous, contradictory and noisy data. It needs to learn through its own interaction with the world, being able to assess events with respect to the goal it is trying to achieve, and to alter its behavior if necessary. Chapter 4 presents mechanisms that can support these fundamental learning competencies.

Mobility is (almost) pointless without the ability of goal-directed motion, i.e. navigation. This book will therefore cover the area of mobile robot navigation, taking some inspiration from the most successful navigators on earth: living beings (chapter 5). Five case studies highlight the mechanisms used in successful robot navigation systems: self-organization, emergent functionality and autonomous mapping of the environment "as the robot perceives it".

Scientific research is not only about matter, it is about method as well. Given the complexity of robot-environment interaction, given the sensitivity of a robot's sensors to slight changes in the environment, to color and surface structure of objects, etc., to date the proof of a robot control program is still in physical experiments. To know what robot behavior will result from a specific robot control program, one actually has to run the program on a real robot. Numerical models of the complex interaction between robot and environment interaction are still imprecise approximations, due to the sensitivity of robot sensors to variations in environmental conditions. However, chapter 6 looks at one approach to construct a more faithful model of robot-environment interaction, and at the conditions under which such modeling is achievable.

The purpose of this book is not only to give an introduction to the construction of mobile robots and the design of intelligent controllers, but also to demonstrate methods of evaluation of autonomous mobile robots - the science of mobile robotics. Scientific method involves the analysis of existing knowledge, identification of open questions, the design of an appropriate experimental procedure to investigate the question, and the analysis of the results.

In established natural sciences this procedure has been refined over decades and is now well understood, but in the relatively young science of robotics this is not the case. There are no universally agreed procedures yet, neither for conducting experiments, nor for the interpretation of results. Environments, robots and their tasks cannot yet be described in unambiguous ways that allow independent replication of experiments and independent verification of results. Instead, qualitative descriptions of experiments and results have to be used. Widely accepted standard benchmark tests in the area of mobile robotics do not exist, and existence proofs, i.e. the implementation of one particular algorithm on one particular robot, operating in one particular environment, are the norm.

To develop a science of autonomous mobile robotics, quantitative descriptions of robots, tasks and environments are needed, and independent replication and verification of experiments has to become the standard procedure within the scientific community. Existence proofs alone will not suffice to investigate mobile robots systematically. They serve a purpose in the early stages of the emergence of a scientific field, but have to be supplemented later by rigorous and quantitatively defined experimentation. Chapter 7 therefore discusses mathematical tools that allow such quantitative assessment of robot performance, and gives three case studies of quantitative analysis of mobile robot behavior.

The book concludes with an analysis of the reasons for successes in mobile robotics research, and identifies technological, control and methodological challenges that lie ahead.

Mobile robotics is a vast research area, with many more facets than this introductory textbook can cover. The purpose of this book is to whet your appetite for mobile robotics research. Each chapter of this book includes pointers to further reading, and world-wide web links, in addition to the references given in the text. Using these, you will hopefully agree that mobile robotics is indeed a fascinating research topic that throws some light on the age-old question:

"What are the fundamental building blocks of intelligent behavior?"



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