Performance Measurement Under Increasing Environmental Uncertainty In The Context of Interval Type-2 Fuzzy Logic Based Robotic Sailing

TL;DR

This paper evaluates performance measurement methods for fuzzy logic-based robotic sailing controllers under environmental uncertainty, proposing a more robust comparison technique that outperforms traditional measures like RMSE.

Contribution

It introduces a new, sophisticated performance comparison method tailored for uncertain environments, improving robustness over standard metrics.

Findings

The new method provides more consistent performance assessments.

Traditional measures like RMSE are inadequate under high environmental variability.

The approach enhances the reliability of performance comparisons in uncertain conditions.

Abstract

Performance measurement of robotic controllers based on fuzzy logic, operating under uncertainty, is a subject area which has been somewhat ignored in the current literature. In this paper standard measures such as RMSE are shown to be inappropriate for use under conditions where the environmental uncertainty changes significantly between experiments. An overview of current methods which have been applied by other authors is presented, followed by a design of a more sophisticated method of comparison. This method is then applied to a robotic control problem to observe its outcome compared with a single measure. Results show that the technique described provides a more robust method of performance comparison than less complex methods allowing better comparisons to be drawn.