NASA space station automation: AI-based technology review

Research and Development projects in automation for the Space Station are discussed. Artificial Intelligence (AI) based automation technologies are planned to enhance crew safety through reduced need for EVA, increase crew productivity through the reduction of routine operations, increase space station autonomy, and augment space station capability through the use of teleoperation and robotics. AI technology will also be developed for the servicing of satellites at the Space Station, system monitoring and diagnosis, space manufacturing, and the assembly of large space structures

Model-Based Probabilistic Reasoning for Electronics Troubleshooting

1N-ATE is an on-going project aimed at developing expert consultant systems for guiding a novice technician through each step of an electronics troubleshooting session. One goal of the project is to automatically produce, given a set of initial symptoms, a binary (pass/fail) decision tree of testpoints to be checked by the technician. This paper discusses our initial approach using a modified game tree search technique, the gamma miniaverage method. One of the parameters which guides this search technique- the cost of each test- is stored a priori The two other parameters that guide it- the conditional probability of test outcomes and the proximity to a solution- are provided by a dynamic model of an expert troubleshooter's beliefs about what in the device is good and what is bad. This model of beliefs is updated using probabilistic "tp.st-resuLt ► plausible-consequences " rules These rules are either provided by an expert technician, or approximated by a model-guided Rule Generator The model that guides the generation of rules is a simple block diagram of the Unit Under Test (UUT) augmented with component failure rates. 1