Planning for execution monitoring on a planetary rover

A planetary rover will be traversing largely unknown and often unknowable terrain. In addition to geometric obstacles such as cliffs, rocks, and holes, it may also have to deal with non-geometric hazards such as soft soil and surface breakthroughs which often cannot be detected until rover is in imminent danger. Therefore, the rover must monitor its progress throughout a traverse, making sure to stay on course and to detect and act on any previously unseen hazards. Its onboard planning system must decide what sensors to monitor, what landmarks to take position readings from, and what actions to take if something should go wrong. The planning systems being developed for the Pathfinder Planetary Rover to perform these execution monitoring tasks are discussed. This system includes a network of planners to perform path planning, expectation generation, path analysis, sensor and reaction selection, and resource allocation

Reasoning About Knowledge Using Extensional Logics

When representing statements about knowledge in a extensional logic, it occasionally happens that undesired conclusions arise. Such extraneous conclusions are often the result of substitution of equals for equals or existential instantiation within intensional operators such as Know. In the past, efforts at solving this problem have centered on modifications to the logic. In this thesis, I propose a solution that leaves the logic intact and changes the representation of the statements instead. The solution presented here has four main points: 1) Only propositions can be known. 2) Relations rather than functions should be used to describe objects. 3) Temporal reasoning is often necessary to represent many real-world problems. 4) In cases where more than one label can apply to the same object, an agent's knowledge about labels must be explicitly represented. When these guidelines are followed, statements about knowledge can be represented in standard first-order predicate logic in such a way that extraneous conclusions cannot be drawn. Standard first-order theorem provers (like Prolog) can then be used to solve problems which involve reasoning about knowledge

Adaptable state based control system

An autonomous controller, comprised of a state knowledge manager, a control executor, hardware proxies and a statistical estimator collaborates with a goal elaborator, with which it shares common models of the behavior of the system and the controller. The elaborator uses the common models to generate from temporally indeterminate sets of goals, executable goals to be executed by the controller. The controller may be updated to operate in a different system or environment than that for which it was originally designed by the replacement of shared statistical models and by the instantiation of a new set of state variable objects derived from a state variable class. The adaptation of the controller does not require substantial modification of the goal elaborator for its application to the new system or environment

Towards principled experimental study of autonomous mobile robots

We review the current state of research in autonomous mobile robots and conclude that there is an inadequate basis for predicting the reliability and behavior of robots operating in unengineered environments. We present a new approach to the study of autonomous mobile robot performance based on formal statistical analysis of independently reproducible experiments conducted on real robots. Simulators serve as models rather than experimental surrogates. We demonstrate three new results: 1) Two commonly used performance metrics (time and distance) are not as well correlated as is often tacitly assumed. 2) The probability distributions of these performance metrics are exponential rather than normal, and 3) a modular, object-oriented simulation accurately predicts the behavior of the real robot in a statistically significant manner. 1