Title :
Multi-sensor fusion: a perspective
Author :
Hackett, Jay K. ; Shah, Mubarak
Author_Institution :
Dept. of Comput. Sci., Central Florida Univ., Orlando, FL, USA
Abstract :
A survey of the state of the art in multisensor fusion is presented. Papers related to fusion have been surveyed and classified into six categories: scene segmentation, representation, 3-D shape, sensor modeling, autonomous robots, and object recognition. A number of fusion strategies have been employed to combine sensor outputs. These strategies range from simple set intersection, logical and operations, and heuristic production rules to more complex methods involving nonlinear least-squares fits and maximum-likelihood estimates. Sensor uncertainty has been modeled using Bayesian probabilities and support and plausibility involving the Dempster-Shafer formalism
Keywords :
Bayes methods; pattern recognition; picture processing; probability; Bayesian probabilities; Dempster-Shafer formalism; autonomous robots; heuristic production rules; maximum-likelihood estimates; multisensor fusion; nonlinear least-squares fits; object recognition; pattern recognition; picture processing; scene segmentation; sensor modeling; set intersection; Computer science; Layout; Manufacturing automation; Robot sensing systems; Robotics and automation; Sensor fusion; Sensor phenomena and characterization; Sensor systems; Tactile sensors; Target recognition;
Conference_Titel :
Robotics and Automation, 1990. Proceedings., 1990 IEEE International Conference on
Conference_Location :
Cincinnati, OH
Print_ISBN :
0-8186-9061-5
DOI :
10.1109/ROBOT.1990.126184
