Artificial Evolution Based Autonomous Robot Navigation

Modern robots are required to carry out work in unstructured dynamic human environments. In the recent decades, the application of artificial evolution to autonomous mobile robots to enable them to adapt their behaviors to changes of the environments has attracted much attention. As a result, an infant research field called evolutionary robotics has been rapidly developed that is primarily concerned with the use of artificial evolution techniques for the automatic design of adaptive robots. As an innovative and effective solution to autonomous robot controller design, it can derive adaptive robotic controllers capable of elegantly dealing with continuous changes in unstructured environments in real time. In the chapter, the basic concepts regarding artificial evolution and evolutionary robotics are introduced, and then a variety of successful applications of artificial evolution in autonomous robot navigation along the dimension of artificial evolution adopted are surveyed and discussed. Open issues and future research in this field are also presented.

[1]  Gaurav S. Sukhatme,et al.  Robots: Intelligence, Versatility, Adaptivity , 2002 .

[2]  Marco Dorigo,et al.  Genetics-based machine learning and behavior-based robotics: a new synthesis , 1993, IEEE Trans. Syst. Man Cybern..

[3]  Stefano Nolfi,et al.  How to Evolve Autonomous Robots: Different Approaches in Evolutionary Robotics , 1994 .

[4]  John H. Holland,et al.  Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence , 1992 .

[5]  Rodney A. Brooks,et al.  Artificial Life and Real Robots , 1992 .

[6]  Oliver Brock,et al.  Robotics and interactive simulation , 2002, CACM.

[7]  Gaurav S. Sukhatme,et al.  Embedding robots into the Internet , 2000, Commun. ACM.

[8]  Hermann Kopetz,et al.  Software engineering for real-time: a roadmap , 2000, ICSE '00.

[9]  Zack J. Butler,et al.  Self-reconfiguring robots , 2002, CACM.

[10]  Francesco Mondada,et al.  Evolution of homing navigation in a real mobile robot , 1996, IEEE Trans. Syst. Man Cybern. Part B.

[11]  David E. Goldberg,et al.  Genetic Algorithms in Search Optimization and Machine Learning , 1988 .

[12]  Luc Steels,et al.  Discovering the Competitors , 1996, Adapt. Behav..

[13]  John J. Grefenstette,et al.  Incremental Learning of Control Strategies with Genetic algorithms , 1989, ML.

[14]  Adrian Thompson,et al.  Evolving Electronic Robot Controller that Exploit Hardware Resources , 1995, ECAL.

[15]  Sebastian Thrun,et al.  Probabilistic robotics , 2002, CACM.

[16]  Thomas Röfer,et al.  A Behavior Architecture for Autonomous Mobile Robots Based on Potential Fields , 2004, RoboCup.