Probabilistic analysis applied to robots
2016
Robots are increasingly being used in industry and starting their way to our homes as
well. Nonetheless, the most frequently used techniques to analyze robots motion are based
on simulations or statistical experiments made from filming robots’ movements. In this
work we propose an alternative way of performing such analysis by using Probabilistic
Model Checking with the language and tool PRISM. With PRISM we can perform
simulations as well as check exhaustively whether a robot motion planning satisfies specific
Probabilistic Temporal formulas. Therefore we can measure energy consumption, time to
complete missions, etc., and all of these in terms of specific motion planning algorithms.
As consequence we can also determine if an algorithm is superior to another in certain
metrics. Furthermore, to ease the use of our work, we hide the PRISM syntax by proposing
a more user-friendly DSL. As a consequence, we created a translator from the DSL to
PRISM by implementing the translation rules and also, a preliminary investigation about
its relative completeness by using the grammatical elements generation tool LGen. We
illustrate those ideas with motion planning algorithms for home cleaning robots.
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