|Fuzzy Logic Techniques for Autonomous Vehicle Navigation|
|Dimiter Driankov and Alessandro Saffiotti (Eds)|
In the past decade a critical mass of work that uses fuzzy logic for autonomous vehicle navigation has been reported. Unfortunately, reports of this work are scattered among conference, workshop, and journal publications that belong to different research communities (fuzzy logic, robotics, artificial intelligence, intelligent control) and it is therefore not easily accessible either to the newcomer or to the specialist. As a result, researchers in this area may end up reinventing things while being unaware of important existing work.
We believe that research and applications based on fuzzy logic in the field of autonomous vehicle navigation have now reached a sufficient level of maturity, and that it should be suitably reported to the largest possible group of interested practitioners, researches, and students. On these grounds, we have endeavored to collect some of the most representative pieces of work in one volume to be used as a reference. Our aim was to provide a volume which is more than ``yet another random collection of papers,'' and gives the reader some added value with respect to the individual papers.
In order to achieve this goal we have aimed at:
Selecting contributions which are representative of a wide range of problems and solutions and which have been validated on real robots; and
Setting the individual contributions in a clear framework, that identifies the main problems of autonomous robotics for which solutions based on fuzzy logic have been proposed.
Each chapter in the present collection focuses on one specific problem in the area of autonomous navigation, and illustrates the development procedure and the experimental setting in enough detail to allow others to reproduce the results. Moreover, each chapter emphasizes the role of fuzzy logic in the design, analysis, implementation, and performance evaluation of the proposed solution to the target problem. It also clearly points out the advantages and disadvantages of using fuzzy logic for the specific problem addressed.
The volume is aimed at readers with some knowledge of mobile robotics but possibly very little knowledge of fuzzy logic. Thus, the volume includes a ``hands-on'' quick introduction to fuzzy logic and fuzzy control. Readers already familiar with these subjects will find with each contribution clear pointers to literature sources where they can find details about the specific fuzzy techniques used. For readers who are unfamiliar with robotics, the problems related to autonomous navigation are systematized and described in such a way so that the reader can understand the main difficult issues. To all our readers we recommend a look at http://www.aass.oru.se/Living/FLAR/ where we maintain a set of resources on fuzzy logic in autonomous robotics.
The volume is structured in five parts. The first part contains two tutorial chapters which introduce the reader to the problems of autonomous vehicle navigation, and to fuzzy logic, respectively. The first chapter also acts as an introduction to the volume, by presenting the framework that has been used to structure this collection. The following four parts deal with the four issues identified by this framework: the design of robust individual navigation behaviors; the coordination between several independent navigation behaviors; the use of sensor data and prior knowledge to build and maintain a global map of the environment; and the integration between the different levels of representation and reasoning that must be present in an autonomous vehicle.
|Örebro, Sweden||Dimiter Driankov|
|July 2000||Alessandro Saffiotti|