A Reactive Model-based Programming Language for Robotic Space Explorers

Michel Ingham, Robert Ragno, and Brian Williams, A Reactive Model-based Programming Language for Robotic Space Explorers, Proceedings of the 6th International Symposium on Artificial Intelligence, Robotics and Automation in Space, Montreal, Canada, June 2001.

Model-based autonomous agents have emerged recently as vital technologies in the development of highly autonomous reactive systems, particularly in the aerospace domain. These agents utilize many automated reasoning capabilities, but are complicated to use because of the variety of languages employed for each capability. To address this problem, we introduce model-based programming, a novel approach to designing embedded software systems. In particular, we introduce the Reactive Model-based Programming Language (RMPL), which provides a framework for constraint-based modeling, as well as a suite of reactive programming constructs. To convey the expressiveness of RMPL, we show how it captures the main features of synchronous programming languages and advanced robotic execution languages.

Reactive programming has been discussed on LtU quite a bit in the past. Functional reactive programming, in particular, has got a lot of attention. But I don't think we've covered reactive model-based programming before. This is an interesting approach that combines constraint-based modeling with reactive programming, and compiles programs down to hierarchical constraint automata for execution. Whereas reactive languages like Esterel focus on manipulating signals, RMPL works by manipulating (potentially hidden) system states.

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Recent progress?

It does look very interesting. It'd be good to play with an implementation. Publications seem to have halted around 2003 according to the CSAIL publications list, pending a C/C++ re-write to ease embedding.


Brian Williams' MERS research group still seems to be active, although from their recent publications their focus appears to have shifted from RMPL development to applications of model-based programming.