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Theory and experiments in SmartNav rover navigation

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This paper describes theoretical and experimental results using the SmartNav rule-free fuzzy rover navigation system. SmartNav divides the terrain perceived by the rover into a number of circular sectors, and evaluates each sector using goal and safety preference factors to differentiate between preferred and unpreferred terrain sectors. The goal-preference factor is used to make sector evaluation based on the sector orientation relative to the designated goal position. The safety-preference factors are used to make sector evaluations on the basis of the sector local and regional terrain hazards. Three methods are developed to blend the three sector evaluations in order to find the effective preference factor for each sector. Two sector selection methods are then described in which the sector preference factors are used to find the heading command for the rover. The rover speed command is also computed based on the goal distance and safety-preference factor of the chosen sector. The above navigation steps are continuously repeated throughout the rover motion. Experimental results are presented to demonstrate the navigational capabilities of SmartNav using a commercial Pioneer 2AT rover traversing a simulated Martian terrain at the JPL Mini Mars Yard.

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  1. The reason for using a non-zero value for α is to penalize, but not to completely eliminate, a sector based on its goal misalignment.

  2. There are different implementations of the fuzzy intersection (AND) operation. For instance, using the product implementation of AND, we obtain \(f_s = f_l*f_r\), in which case \(f_s \leq {\rm Min}\{f_l, f_r\}\).

  3. This method is conceptually similar to a defuzzification method in fuzzy logic (Pfluger et al., 1992).


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The research described in this paper was performed at the Jet Propulsion Laboratory, California Institute of Technology, under contract with the National Aeronautics and Space Administration

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Seraji, H., Werger, B. Theory and experiments in SmartNav rover navigation. Auton Robot 22, 165–182 (2007).

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