Difference between revisions of "EECI 2012: Computer Session: TuLiP"

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==  Lecture Materials ==
==  Lecture Materials ==
* Lecture slides: [http://www.cds.caltech.edu/~utopcu/AFRL2012/C2_TuLiP.pdf TuLiP] (Exercises are at the end of the slides.)
* Lecture slides: [http://dl.dropbox.com/u/29005314/C2_tulip-17May12.pdf TuLiP] (Exercises are at the end of the slides.)
* MATLAB plotting: [http://www.cds.caltech.edu/~murray/courses/afrl-sp12/plotNineCell.m
* MATLAB plotting: [http://dl.dropbox.com/u/29005314/plotRobotSim.m plotRobotSim.m], [http://dl.dropbox.com/u/29005314/plotCarSim.m plotCarSim.m]
* Nine cell example: [http://www.cds.caltech.edu/~murray/courses/afrl-sp12/plotNineCell.m plotNineCell.m], [http://www.cds.caltech.edu/~murray/courses/afrl-sp12/nine_cell0.py nine_cell0.py], [http://www.cds.caltech.edu/~murray/courses/afrl-sp12/nine_cell_sim.txt nine_cell_sim.txt]
* [http://dl.dropbox.com/u/29005314/tulip_examples.zip Example TuLiP files] (zip file):
* Intersection example: [http://www.cds.caltech.edu/~murray/courses/afrl-sp12/plotIntersection.m plotIntersection.m], [http://www.cds.caltech.edu/~murray/courses/afrl-sp12/intersection0.py intersectionl0.py], [http://www.cds.caltech.edu/~murray/courses/afrl-sp12/intersection_sim.txt intersection_sim.txt]
** 6 cell robot, discrete state space: [http://dl.dropbox.com/u/29005314/robot_discrete_simple.py robot_discrete_simple.py]
** 6 cell robot, with dynamics: [http://dl.dropbox.com/u/29005314/robot_simple.py robot_simple.py], [http://dl.dropbox.com/u/29005314/robot_simple2.py robot_simple2.py] (alternative formulation)


== Further Reading ==
== Further Reading ==

Revision as of 04:49, 10 May 2012

Return to Caltech/AFRL 2012 Main Page

This lecture provides an overview of TuLiP, a Python-based software toolbox for the synthesis of embedded control software that is provably correct with respect to a GR[1] specifications. TuLiP combines routines for (1) finite state abstraction of control systems, (2) digital design synthesis from GR[1] specifications, and (3) receding horizon planning. The underlying digital design synthesis routine treats the environment as adversary; hence, the resulting controller is guaranteed to be correct for any admissible environment profile. TuLiP applies the receding horizon framework, allowing the synthesis problem to be broken into a set of smaller problems, and consequently alleviating the computational complexity of the synthesis procedure, while preserving the correctness guarantee.

A brief overview of TuLiP will be followed by hands-on exercises using the toolbox.


Lecture Materials

Further Reading

  • TuLiP: A Software Toolbox for Receding Horizon Temporal Logic Planning, T. Wongpiromsarn, U. Topcu, N. Ozay, H. Xu and R. M. Murray, Hybrid Systems: Computation and Control, 2011.

Additional Information

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