Title :
Model-based multi-sensor data fusion
Author :
Wen, W. ; Durrant-Whyte, H.F.
Author_Institution :
Dept. of Eng. Sci., Oxford Univ., UK
Abstract :
The authors describe an algorithm for implementing a multisensor system in a model-based environment with consideration of the constraints. Based on an environment model, geometric features and constraints are generated from a CAD model database. Sensor models are used to predict sensor response to certain features and to interpret raw sensor data. A constrained MMS (minimum mean squared) estimator is used to recursively predict, match, and update feature location. The effects of applying various constraints in estimation were shown by simulation system mounted on a robot arm for localization of known object features
Keywords :
constraint handling; feature extraction; filtering and prediction theory; sensor fusion; CAD model database; constrained minimum mean squared estimator; environment model; feature location; geometric features; model based multisensor data fusion; sensor response; sonar; Covariance matrix; Fusion power generation; Mobile robots; Navigation; Predictive models; Robot sensing systems; Sensor fusion; Sensor phenomena and characterization; Sensor systems; Solid modeling;
Conference_Titel :
Robotics and Automation, 1992. Proceedings., 1992 IEEE International Conference on
Conference_Location :
Nice
Print_ISBN :
0-8186-2720-4
DOI :
10.1109/ROBOT.1992.220130
