Statistical Evaluation Method for Comparing Grid Map Based Sensor Fusion Algorithms. Academic Article uri icon

abstract

  • In this paper we present a method for evaluating sensor fusion al- gorithms based on a quantitative comparison, which is independent of the data acquired and the sensors used. The sensor fusion per- formance measures and performance analysis procedure provide a basis for modeling, analyzing, experimenting, and comparing dif- ferent sensor fusion algorithms. The capability to compare different algorithms creates a ranking basis, making it possible to select the best algorithm. The statistical evaluation method defines the exper- imental design and statistical analysis. The numbers of experiments and repetitions required are derived from the statistical character- istics and the desired confidence level. Since procedures are defined to ensure that the experiments are indeed conducted differently, the results are not specific for either the evaluated test cases or the sensor characteristics. The statistical analysis provides a system- atic method for comparing sensor fusion algorithms. Although this method requires experimentation, it offers the ability to compare ac- tual performances in the real world. Quantitative procedures are developed to ensure that specific environmental conditions evalu- ated do not influence the evaluation. To demonstrate the statistical evaluation method it is applied to a case study that compared five different sensor fusion algorithms in a mobile robot experiment. KEY WORDS—evaluation method, mobile robots, perfor- mance measures, sensor fusion

publication date

  • January 1, 2006