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Firby, R. James

Publications and source records attributed to Firby, R. James.

Complex Event Recognition Architecture

Complex Event Recognition Architecture (CERA) is the name of a computational architecture, and software that implements the architecture, for recognizing complex event patterns that may be spread across multiple streams of input data. One of the main components of CERA is an intuitive event pattern language that simplifies what would otherwise be the complex, difficult tasks of creating logical descriptions of combinations of temporal events and defining rules for combining information from different sources over time. In this language, recognition patterns are defined in simple, declarative statements that combine point events from given input streams with those from other streams, using conjunction, disjunction, and negation. Patterns can be built on one another recursively to describe very rich, temporally extended combinations of events. Thereafter, a run-time matching algorithm in CERA efficiently matches these patterns against input data and signals when patterns are recognized. CERA can be used to monitor complex systems and to signal operators or initiate corrective actions when anomalous conditions are recognized. CERA can be run as a stand-alone monitoring system, or it can be integrated into a larger system to automatically trigger responses to changing environments or problematic situations.

Fitzgerald, William A.

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.

Gat, Erann

Task directed sensing

High-level robot control research must confront the limitations imposed by real sensors if robots are to be controlled effectively in the real world. In particular, sensor limitations make it impossible to maintain a complete, detailed world model of the situation surrounding the robot. To address the problems involved in planning with the resulting incomplete and uncertain world models, traditional robot control architectures must be altered significantly. Task-directed sensing and control is suggested as a way of coping with world model limitations by focusing sensing and analysis resources on only those parts of the world relevant to the robot's active goals. The RAP adaptive execution system is used as an example of a control architecture designed to deploy sensing resources in this way to accomplish both action and knowledge goals.

Firby, R. James

Path planning and execution monitoring for a planetary rover

A path planner and an execution monitoring planner that will enable the rover to navigate to its various destinations safely and correctly while detecting and avoiding hazards are described. An overview of the complete architecture is given. Implementation and testbeds are described. The robot can detect unforseen obstacles and take appropriate action. This includes having the rover back away from the hazard and mark the area as untraversable in the in the rover's internal map. The experiments have consisted of paths roughly 20 m in length. The architecture works with a large variety of rover configurations with different kinematic constraints.

Gat, Erann