Title :
On comparing statistical and set-based methods in sensor data fusion
Author :
Hager, Gregory D. ; Engelson, Sean P. ; Atiya, Sami
Author_Institution :
Dept. of Comput. Sci., Yale Univ., New Haven, CT, USA
Abstract :
The theoretical and practical considerations of two common sensor data fusion methodologies (set based and statistically based parameter estimation) are compared. Their convergence behavior for a variety of simulated problems is examined. Robot localization systems implemented using both methods are described, and their performance is compared. It is concluded that set-based methods have performance that sometimes exceeds that of statistical methods, although this result is highly problem-dependent. These problem dependencies are characterized
Keywords :
convergence; parameter estimation; robots; sensor fusion; set theory; statistics; convergence; robot localisation systems; sensor data fusion; set-based methods; statistically based parameter estimation; Computational modeling; Computer science; Convergence; Parameter estimation; Robot localization; Sensor fusion; Sensor systems; Solid modeling; Statistical analysis; Uncertainty;
Conference_Titel :
Robotics and Automation, 1993. Proceedings., 1993 IEEE International Conference on
Conference_Location :
Atlanta, GA
Print_ISBN :
0-8186-3450-2
DOI :
10.1109/ROBOT.1993.292170
