90165-2 Increasingly, applications require computers to interface with the real world and draw data directly from it. These applications range from defense to medicine, manufacturing to environmental health. They all depend on inputs that are noisy, incomplete, and of limited accuracy. This book introduces multi-sensor fusion, which has emerged as the method of choice for implementing robust systems that can handle imperfect inputs. It represents the first broad, practical text on the subject - covering all the technologies and methods associated with multi-sensor fusion, including: *Multidimensional data structures *Techniques for reasoning with uncertainty *Approaches to enhancing system dependability *Working with meta-heuristics The book reflects six years of sensor fusion research for the Office of Naval Research, introducing novel solutions to challenges such as image registration, distributed agreement, and sensor selection. Multi-Sensor Fusion focuses extensively on applications, including neural networks, genetic algorithms, tabu search and simulated annealing. It comes with a set of functioning C programs on disk to implement these applications.This Sensor Fusion Toolkit includes both a standard Kalman filter and the authors' enhanced Distributed Dynamic Sensor Fusion algorithm, which is easier to use and solves more problems. This is the essential tutorial and reference for any professional or advanced student developing systems that utilize sensor input, including computer scientists, electrical, mechanical and chemical engineers.