Optimal matching algorithm for multidimensional sensor readings

Richard Ree Brooks; S. Sitharama Iyengar

doi:10.1117/12.220948

15 September 1995 Optimal matching algorithm for multidimensional sensor readings

Richard Ree Brooks, S. Sitharama Iyengar

Proceedings Volume 2589, Sensor Fusion and Networked Robotics VIII; (1995) https://doi.org/10.1117/12.220948
Event: Photonics East '95, 1995, Philadelphia, PA, United States

Abstract

Multisensor fusion is a method which is of current importance for improving sensor reliability. Because individual sensors are prone to transient errors, mechanical failures, and noise, as well as being of limited accuracy, it is advisable to fuse readings from many heterogeneous sensors. This allows several different sensor technologies to be used together to measure the value of a physical variable. Using a multitude of sensor technologies makes the overall system less sensitive to the failures of any one technology. Unfortunately, it is a non-trivial task to glean the best interpretation from a large number of partially contradictory sensor readings. A number of methods exist for finding the best approximate match for this type of redundant, but possibly faulty, data. This paper presents a new algorithm which finds the best possible interpretation of partially contradictory sensor readings, some of which are incorrect, that contain data of greater than two dimensions. Currently available algorithms return interpretations which are larger than the optimal. This has been done to avoid excessive computational complexity. The algorithm presented here is based on data structures from computational geometry and provides the smallest possible region satisfying the constraints of the problem with a reasonable computational complexity.

Citation Download Citation

Richard Ree Brooks and S. Sitharama Iyengar "Optimal matching algorithm for multidimensional sensor readings", Proc. SPIE 2589, Sensor Fusion and Networked Robotics VIII, (15 September 1995); https://doi.org/10.1117/12.220948

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