Integration, Coordination and Control of Multi-Sensor Robot Systems / Edition 1

by Hugh F. Durrant-Whyte

Overview

Overview Recent years have seen an increasing interest in the development of multi-sensory robot systems. The reason for this interest stems from a realization that there are fundamental limitations on the reconstruction of environment descriptions using only a single source of sensor information. If robot systems are ever to achieve a degree of intelligence and autonomy, they must be capable of using many different sources of sensory information in an active and dynamic manner. The observations made by the different sensors of a multi-sensor system are always uncertain, usually partial, occasionally spuri9us or incorrect and often geographically or geometrically imcomparable with other sensor views. The sensors of these systems are characterized by the diversity of information that they can provide and by the complexity of their operation. It is the goal of a multi­ sensor system to combine information from all these different sources into a robust and consistent description of the environment.

Product Details

ISBN-13:	9780898382471
Publisher:	Springer US
Publication date:	11/30/1987
Series:	The Springer International Series in Engineering and Computer Science , #36
Edition description:	1988
Pages:	236
Product dimensions:	6.10(w) x 9.25(h) x 0.02(d)

Table of Contents

1 Introduction.- 1.1 Sensors and Intelligent Robotics.- 1.2 Multi-Sensor Robot Systems.- 1.3 Organization of Sensor Systems.- 1.4 The Integration of Sensory Information.- 1.5 Coordination of Sensor Systems.- 1.6 Summary and Overview.- 2 Environment Models and Sensor Integration.- 2.1 Introduction.- 2.2 Geometric Environment Models.- 2.3 Uncertain Geometry.- 2.4 Characterizing Uncertain Geometry.- 2.5 Manipulating Geometric Uncertainty.- 2.6 Gaussian Geometry.- 2.7 Gaussian Topology.- 2.8 Summary.- 3 Sensors and Sensor Models.- 3.1 Introduction.- 3.2 Characterizing Sensors.- 3.3 Multi-Sensor System Models.- 3.4 Sensors as Team Members.- 3.5 Observation Models.- 3.6 Dependency Models.- 3.7 State Models.- 3.8 Summary.- 4 Integrating Sensor Observations.- 4.1 Introduction.- 4.2 Decision Models and Information Fusion.- 4.3 Integrating Observations with Constraints.- 4.4 Estimating Environment Changes.- 4.5 Consistent Integration of Geometric Observations.- 4.6 Summary.- 5 Coordination and Control.- 5.1 Introduction.- 5.2 The Team Decision Problem.- 5.3 Multi-Sensor Teams.- 5.4 Sensor Control.- 5.5 Summary.- 6 Implementation and Results.- 6.1 Introduction.- 6.2 A Structure for Multi-Sensor Systems.- 6.3 Experimental Scope.- 6.4 Implementation.- 6.5 Simulation Results.- 6.6 Experimental Results.- 6.7 Summary and Conclusions.- 7 Conclusions.- 7.1 Summary Discussion.