Performance Measurement Under Increasing Environmental Uncertainty In The Context of Interval Type-2 Fuzzy Logic Based Robotic Sailing
This addresses a gap in performance measurement for fuzzy logic-based robotic controllers under uncertainty, but it appears incremental as it builds on existing methods for a specific domain.
The paper tackled the problem of measuring robotic controller performance under increasing environmental uncertainty, showing that standard measures like RMSE are inadequate and proposing a more sophisticated method that provides more robust comparisons in tests.
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.