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We outline a cla�s of problems, typical of Mars rover operations, that are problematic for cur­ rent methods of planning under uncertainty. The existing methods fail because they suffer from one or more of the following limitations: 1) they rely on very simple models of actions and time, 2) they assume that uncertainty is manifested in discrete action(More)
We describe an approach for exploiting structure in Markov Decision Processes with continuous state variables. At each step of the dynamic programming , the state space is dynamically partitioned into regions where the value function is the same throughout the region. We first describe the algorithm for piecewise constant representations. We then extend it(More)
—The Pathfinder mission demonstrated the potential for robotic Mars exploration but at the same time indicated the need for more robust rover autonomy. Future planned missions call for long traverses over unknown terrain, robust navigation and instrument placement, and reliable operations for extended periods of time. Ultimately, missions may visit multiple(More)
We report on a study to determine the maturity of different verification and validation technologies (V&V) on a representative example of NASA flight software. The study consisted of a controlled experiment where three technologies (static analysis, runtime analysis and model checking) were compared to traditional testing with respect to their ability to(More)
This paper presents an approach to building plans using partially observable Markov decision processes. The approach begins with a base solution that assumes full observability. The partially observable solution is incrementally constructed by considering increasing amounts of information from observations. The base solution directs the expansion of the(More)
In this paper, we propose a new method based on Hidden Markov Models to interpret temporal sequences of sensor data from mobile robots to automatically detect features. Hidden Markov Models have been used for a long time in pattern recognition, especially in speech recognition. Their main advantages over other methods (such as neural networks) are their(More)
A surgical intensive care unit (ICU) is a challenging monitoring environment. The multitude of monitored variables, the high frequency of alarms, and the severity of likely complications and emergencies can overload the cognitive skills of even experienced clinicians. ICU monitoring is also complicated by changes in clinical context. Over the course of a(More)
Intelligent monitoring and control involves observing and guiding the behavior of a physical system toward some objective, with real-time constraints on the utility of particular actions. Generic functional requirements for this task include: integration of perception, reasoning , and action; integration of multiple reasoning activities; reasoning about(More)