EECI 2013: Computer Session: TuLiP - Revision history

Murray: /* Lecture Materials */

2014-03-02T18:04:58Z

Lecture Materials

← Older revision		Revision as of 18:04, 2 March 2014
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	== Lecture Materials ==		== Lecture Materials ==
	* Lecture slides: [http://www.cds.caltech.edu/~~~utopcu~~/~~eeci13~~/~~C2_TuLiP~~-~~2013~~.pdf TuLiP]		* Lecture slides: [http://www.cds.caltech.edu/~murray/courses/eeci-sp13/C2_tulip-21Mar13.pdf TuLiP]
	* MATLAB plotting: [http://www.cds.caltech.edu/~murray/courses/eeci-sp12/plotRobotSim.m plotRobotSim.m], [http://www.cds.caltech.edu/~murray/courses/eeci-sp12/plotCarSim.m plotCarSim.m]		* MATLAB plotting: [http://www.cds.caltech.edu/~murray/courses/eeci-sp12/plotRobotSim.m plotRobotSim.m], [http://www.cds.caltech.edu/~murray/courses/eeci-sp12/plotCarSim.m plotCarSim.m]
	* [http://www.cds.caltech.edu/~murray/courses/eeci-sp12/tulip_examples.zip Example TuLiP files] (zip file):		* [http://www.cds.caltech.edu/~murray/courses/eeci-sp12/tulip_examples.zip Example TuLiP files] (zip file):

Murray at 08:13, 22 March 2013

2013-03-22T08:13:10Z

← Older revision		Revision as of 08:13, 22 March 2013
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	{{eeci-sp13 header\|prev=RHTLP\|next=Advanced ~~Topcis~~}}		{{eeci-sp13 header\|prev=RHTLP\|next=Advanced Topics}}

	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.		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.

Murray at 08:11, 22 March 2013

2013-03-22T08:11:52Z

← Older revision		Revision as of 08:11, 22 March 2013
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	{{eeci-~~sp12~~ header\|prev=RHTLP\|next=Advanced Topcis}}		{{eeci-sp13 header\|prev=RHTLP\|next=Advanced Topcis}}

	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.		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.

Utopcu: /* Lecture Materials */

2013-03-20T19:59:18Z

Lecture Materials

← Older revision		Revision as of 19:59, 20 March 2013
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	== Lecture Materials ==		== Lecture Materials ==
	* Lecture slides: [http://www.cds.caltech.edu/~utopcu/eeci13/C2_TuLiP-2013.pdf TuLiP] ~~(Exercises are at the end of the slides.)~~		* Lecture slides: [http://www.cds.caltech.edu/~utopcu/eeci13/C2_TuLiP-2013.pdf TuLiP]
	* MATLAB plotting: [http://www.cds.caltech.edu/~murray/courses/eeci-sp12/plotRobotSim.m plotRobotSim.m], [http://www.cds.caltech.edu/~murray/courses/eeci-sp12/plotCarSim.m plotCarSim.m]		* MATLAB plotting: [http://www.cds.caltech.edu/~murray/courses/eeci-sp12/plotRobotSim.m plotRobotSim.m], [http://www.cds.caltech.edu/~murray/courses/eeci-sp12/plotCarSim.m plotCarSim.m]
	* [http://www.cds.caltech.edu/~murray/courses/eeci-sp12/tulip_examples.zip Example TuLiP files] (zip file):		* [http://www.cds.caltech.edu/~murray/courses/eeci-sp12/tulip_examples.zip Example TuLiP files] (zip file):

Utopcu at 19:59, 20 March 2013

2013-03-20T19:59:04Z

← Older revision		Revision as of 19:59, 20 March 2013
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	== Lecture Materials ==		== Lecture Materials ==
	* Lecture slides: [http://www.cds.caltech.edu/~~~murray~~/~~courses~~/~~eeci~~-~~sp12/C2_tulip-17May12~~.pdf TuLiP] (Exercises are at the end of the slides.)		* Lecture slides: [http://www.cds.caltech.edu/~utopcu/eeci13/C2_TuLiP-2013.pdf TuLiP] (Exercises are at the end of the slides.)
	* MATLAB plotting: [http://www.cds.caltech.edu/~murray/courses/eeci-sp12/plotRobotSim.m plotRobotSim.m], [http://www.cds.caltech.edu/~murray/courses/eeci-sp12/plotCarSim.m plotCarSim.m]		* MATLAB plotting: [http://www.cds.caltech.edu/~murray/courses/eeci-sp12/plotRobotSim.m plotRobotSim.m], [http://www.cds.caltech.edu/~murray/courses/eeci-sp12/plotCarSim.m plotCarSim.m]
	* [http://www.cds.caltech.edu/~murray/courses/eeci-sp12/tulip_examples.zip Example TuLiP files] (zip file):		* [http://www.cds.caltech.edu/~murray/courses/eeci-sp12/tulip_examples.zip Example TuLiP files] (zip file):

Utopcu at 19:58, 20 March 2013

2013-03-20T19:58:20Z

← Older revision		Revision as of 19:58, 20 March 2013
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	{{eeci-sp12 header\|prev=~~Protocol Synthesis~~\|next=~~RHTLP~~}}		{{eeci-sp12 header\|prev=RHTLP\|next=Advanced Topcis}}

	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.		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.

Utopcu: Created page with "{{eeci-sp12 header|prev=Protocol Synthesis|next=RHTLP}} This lecture provides an overview of TuLiP, a Python-based software toolbox for the synthesis of embedded control soft..."

2013-03-20T19:57:38Z

Created page with "{{eeci-sp12 header|prev=Protocol Synthesis|next=RHTLP}} This lecture provides an overview of TuLiP, a Python-based software toolbox for the synthesis of embedded control soft..."

New page

{{eeci-sp12 header|prev=Protocol Synthesis|next=RHTLP}}

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 ==
* Lecture slides: [http://www.cds.caltech.edu/~murray/courses/eeci-sp12/C2_tulip-17May12.pdf TuLiP] (Exercises are at the end of the slides.)
* MATLAB plotting: [http://www.cds.caltech.edu/~murray/courses/eeci-sp12/plotRobotSim.m plotRobotSim.m], [http://www.cds.caltech.edu/~murray/courses/eeci-sp12/plotCarSim.m plotCarSim.m]
* [http://www.cds.caltech.edu/~murray/courses/eeci-sp12/tulip_examples.zip Example TuLiP files] (zip file):
** 6 cell robot, discrete state space: [http://www.cds.caltech.edu/~murray/courses/eeci-sp12/robot_discrete_simple.py robot_discrete_simple.py]
** 6 cell robot, with dynamics: [http://www.cds.caltech.edu/~murray/courses/eeci-sp12/robot_simple.py robot_simple.py], [http://www.cds.caltech.edu/~murray/courses/eeci-sp12/robot_simple2.py robot_simple2.py] (alternative formulation)

== Further Reading ==

* [http://www.cds.caltech.edu/~murray/papers/2010n_wtoxm11-hscc.html 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 ==
* [http://sourceforge.net/apps/mediawiki/tulip-control/index.php?title=Main_Page TuLiP on SourceForge] 
* [http://tulip-control.sourceforge.net/doc/ TuLiP Documentation] and [http://tulip-control.sourceforge.net/doc/install.html Installation instructions] 
* [http://jtlv.ysaar.net/ JTLV Project Home Site] JTLV provides the framework for the underlying digital design synthesis routine used in TuLiP.