A multisensor decision fusion system for terrain safety assessment
IEEE Transactions on Robotics
ICVR'07 Proceedings of the 2nd international conference on Virtual reality
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Two safety measures for terrain classification are described: safety score and safety grade. The terrain safety score s is a multi-valued quantitative measure in the form of a crisp numeric value in the continuous unit interval [0.0, 1.0], that is, $$0.0 \leq s \leq 1.0$$. The terrain safety grades $$\{S_1,S_2,\ldots,S_n\}$$ are qualitative measures in the form of linguistic fuzzy sets defined by a human expert that cover the ranges of values of s, with adjacent grades having smooth (i.e., non-abrupt) and overlapping boundaries. The safety grade of a terrain segment is inferred from a set of linguistic rules provided by the human expert that relate the terrain qualities to the terrain safety grades. The safety score for the terrain segment is then computed simply from the safety grades in the activated rules. Safety margin of a terrain is also introduced as a quantitative measure of the degree of terrain safety. Validation and confidence in the sensory data are discussed. The terrain safety score and the sensor confidence score are combined and represented by the fused safety/confidence grid. Given the safety/confidence grid of a terrain patch, two new methods for selection of the safest site are presented: Peak-with-High-Neighbors (PHN) and Center-of-Largest-Area (CLA). These two methods are then illustrated by a numerical example. The methods presented in this paper are computationally fast, and are thus strong viable candidates for real-time implementation. Similar fuzzy rule-based terrain classifiers have previously been implemented successfully in rover navigation experiments and spacecraft landing simulations at JPL.