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The Strathprints institutional repository is a digital archive of University of Strathclyde research outputs.

Strathprints serves world leading Open Access research by the University of Strathclyde, including research by the Strathclyde Institute of Pharmacy and Biomedical Sciences (SIPBS), where research centres such as the Industrial Biotechnology Innovation Centre (IBioIC), the Cancer Research UK Formulation Unit, SeaBioTech and the Centre for Biophotonics are based.

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Non deteriministic planning with evidence and paradoxical reasoning theories

Ceriotti, Matteo and Vasile, Massimiliano and Giardini, Giovanni and Massari, Mauro (2006) Non deteriministic planning with evidence and paradoxical reasoning theories. In: 57th International Astronautical Congress, 2006-10-02 - 2006-10-06.

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Abstract

Planetary exploration rovers require high level of autonomy: they should act as much as possible without human intervention. Nevertheless, there are intrinsic uncertainties on activity duration, position of the rover, and other environment characteristics, like soil condition, dust on solar panels, temperature, etc.: disregarding them during planning would bring unreliable plans. A novel, non-deterministic planning approach for autonomous rovers will be presented. Epistemic uncertainties in the models and errors are taken into account in the planning process in order to prevent failures. For each plan, reliability is computed and used to predict the safest one, by means of the Dempster-Shafer Theory of Evidence. In addition, the rover has been endowed with the capability of reallocating its goals. By data-fusing payload and navigation information, it assigns interest values to the existing goals or generates new goals. In this way the planner can choose the most interesting scientific objectives to be analyzed, with limited human intervention, and reallocates its goals autonomously. Dezert-Smarandache Theory of Plausible and Paradoxical Reasoning has been used for information fusion. Finally, some applications to the generation of reliable plans are shown. These tests demonstrate how the planner is able to generate plans that maximize both the reliability and the level of interest.