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Using qualitative reasoning for robot task planning

As robots are called upon to perform increasingly complex tasks, such as intelligent assembly, maintenance, and inspection in space, the problems of efficient task planning, contingency detection, and recovery become increasingly difficult. While work has progressed toward meeting some of these goals for robotic systems another, for the most part unrelated, area of research in artificial intelligence, qualitative reasoning (QR), has simultaneously been addressing similar reasoning tasks for different classes of complex systems. This paper presents some techniques for bridging the gap between the two research areas, QR representations for reasoning about robotic systems, and examples demonstrating some successful results.