ASYNCHRONOUS PRODUCTION SYSTEM FOR CONTROL OF AN AUTONOMOUS MOBILE ROBOT IN REAL-TIME ENVIRONMENT

Abstract

Autonomous robotic systems designed for hazardous environments require the development of onboard real-time knowledge-based systems capable of generating inference-driven responses to asynchronous, external stimuli. Building such real-time expert systems involves the integration of traditional-knowledge engineering methodologies with time-constrained response and control capabilities. To address such requirements, the Asynchronous Production System (APS), which is a rule-based inference engine capable of dynamic and rapid interaction with its environment, is presented. The APS uses a concurrent-event-driven execution mechanism and an external input-data structure to facilitate the monitoring and processing of real-time asynchronous information. The enhanced conflict-resolution strategies and rule-interruptibility features of the APS execution mechanism allows the APS to make efficient use of the onboard system resources. The implementation of the APS involves the development of a shared-memory, multiprocessor architecture operating in MIMD mode.

This articles provides a description of the APS and presents a prototype APS-based expert system developed to handle external emergencies for the HERMIES HB (Hostile Environment Robotic Machine Intelligent Experiment Series) robot. The prototype expert system demonstrates APS' capabilities of handling multiple levels of emergencies and performing knowledge-based recovery after the asynchronous information is processed.