Rather than using traditional artificial intelligence techniques, which are ineffective when applied to the complexities of real-world robot navigaiton, Connell describes a methodology of reconstructing intelligent robots with distributed, multiagent control systems. After presenting this methodology, hte author describes a complex, robust, and successful application-a mobile robot "can collection machine" which operates in an unmodified offifce environment occupied by moving people.

There is much interest in the use of biometrics for verification, identification, and "screening" applications, collectively called biometric authentication. This interest has been heightened because of the threat of terrorism. Biometric authentication systems offer advantages over systems based on knowledge or possession such as unsupervised (legacy) authentication systems based on password/PIN and supervised (legacy) authentication systems based on driver's licences and passports. The most important advantage is increased security: when a person is authenticated based on a biometric, the probability that this person is the originally enrolled person can be statistically estimated or computed in some other way. When a person is authenticated based on a password or even based on human observation, no such probabilities can be determined. Of course, the mere capability to compute this probability is not sufficient, what is needed is that the probability of correct authentication is high and the error probabilities are low. Achieving this probabilistic linking by introducing biometrics in authentication systems brings along many design choices and may introduce additional security loopholes. "Biometrics" examines the many aspects of biometric applications that are an issue even before a particular biometrics has been selected. In addition, the book further studies many issues that are associated with the currently popular biometric identifiers, namely, finger, face, voice, iris, hand (geometry) and signature.

Starting with fingerprints more than a hundred years ago, there has been ongoing research in biometrics. Within the last forty years face and speaker recognition have emerged as research topics. However, as recently as a decade ago, biometrics itself did not exist as an independent field. Each of the biometric-related topics grew out of different disciplines. For example, the study of fingerprints came from forensics and pattern recognition, speaker recognition evolved from signal processing, the beginnings of face recognition were in computer vision, and privacy concerns arose from the public policy arena. One of the challenges of any new field is to state what the core ideas are that define the field in order to provide a research agenda for the field and identify key research problems. Biometrics has been grappling with this challenge since the late 1990s. With the matu ration of biometrics, the separate biometrics areas are coalescing into the new discipline of biometrics. The establishment of biometrics as a recognized field of inquiry allows the research community to identify problems that are common to biometrics in general. It is this identification of common problems that will define biometrics as a field and allow for broad advancement."