research-article

Receding horizon control for temporal logic specifications

Authors:

Tichakorn Wongpiromsarn,

Richard M. MurrayAuthors Info & Claims

HSCC '10: Proceedings of the 13th ACM international conference on Hybrid systems: computation and control

Pages 101 - 110

https://doi.org/10.1145/1755952.1755968

Published: 12 April 2010 Publication History

Abstract

In this paper, we describe a receding horizon framework that satisfies a class of linear temporal logic specifications sufficient to describe a wide range of properties including safety, stability, progress, obligation, response and guarantee. The resulting embedded control software consists of a goal generator, a trajectory planner, and a continuous controller. The goal generator essentially reduces the trajectory generation problem to a sequence of smaller problems of short horizon while preserving the desired system-level temporal properties. Subsequently, in each iteration, the trajectory planner solves the corresponding short-horizon problem with the currently observed state as the initial state and generates a feasible trajectory to be implemented by the continuous controller. Based on the simulation property, we show that the composition of the goal generator, trajectory planner and continuous controller and the corresponding receding horizon framework guarantee the correctness of the system. To handle failures that may occur due to a mismatch between the actual system and its model, we propose a response mechanism and illustrate, through an example, how the system is capable of responding to certain failures and continues to exhibit a correct behavior.

References

[1]

DARPA Urban Challenge. http://www.darpa.mil/grandchallenge/index.asp, 2007.

[2]

D. Conner, H. Kress-Gazit, H. Choset, A. Rizzi, and G. Pappas. Valet parking without a valet. In Proc. of IEEE/RSJ International Conference on Intelligent Robots and Systems, pages 572--577, 2007.

[3]

E. A. Emerson. Temporal and modal logic. In Handbook of theoretical computer science (vol. B): formal models and semantics, pages 995--1072. MIT Press, Cambridge, MA, USA, 1990.

Digital Library

[4]

A. Girard, A. A. Julius, and G. J. Pappas. Approximate simulation relations for hybrid systems. Discrete Event Dynamic Systems, 18(2):163--179, 2008.

Digital Library

[5]

A. Girard and G. J. Pappas. Brief paper: Hierarchical control system design using approximate simulation. Automatica, 45(2):566--571, 2009.

Digital Library

[6]

G. C. Goodwin, M. M. Seron, and J. A. D. Dona. Constrained Control and Estimation: An Optimisation Approach. Springer, 2004.

Digital Library

[7]

M. Huth and M. Ryan. Logic in Computer Science: Modelling and Reasoning about Systems. Cambridge University Press, 2nd edition, 2004.

Digital Library

[8]

A. Jadbabaie. Nonlinear Receding Horizon Control: A Control Lyapunov Function Approach. PhD thesis, California Institute of Technology, 2000.

[9]

S. Karaman and E. Frazzoli. Sampling-based motion planning with deterministic µ-calculus specifications. In Proc. of IEEE Conference on Decision and Control, Dec. 2009.

[10]

M. Kloetzer and C. Belta. A fully automated framework for control of linear systems from temporal logic specifications. IEEE Transaction on Automatic Control, 53(1):287--297, 2008.

[11]

H. Kress-Gazit, G. Fainekos, and G. Pappas. Where's waldo? Sensor-based temporal logic motion planning. In Proc. of IEEE International Conference on Robotics and Automation, pages 3116--3121, April 2007.

[12]

H. Kress-Gazit and G. J. Pappas. Automatically synthesizing a planning and control subsystem for the DARPA Urban Challenge. In IEEE International Conference on Automation Science and Engineering, pages 766--771, 2008.

[13]

Z. Manna and A. Pnueli. The temporal logic of reactive and concurrent systems. Springer-Verlag, 1992.

Digital Library

[14]

D. Mayne, J. Rawlings, C. Rao, and P. Scokaert. Constrained model predictive control: Stability and optimality. Automatica, 36:789--814(26), June 2000.

Digital Library

[15]

M. B. Milam, K. Mushambi, and R. M. Murray. A new computational approach to real-time trajectory generation for constrained mechanical systems. In Proc. of IEEE Conference on Decision and Control, pages 845--851, 2000.

[16]

R. M. Murray, J. Hauser, A. Jadbabaie, M. B. Milam, N. Petit, W. B. Dunbar, and R. Franz. Online control customization via optimization-based control. In Software-Enabled Control: Information Technology for Dynamical Systems, pages 149--174. Wiley-Interscience, 2002.

[17]

N. Piterman, A. Pnueli, and Y. Sa'ar. Synthesis of reactive(1) designs. In Verification, Model Checking and Abstract Interpretation, volume 3855 of Lecture Notes in Computer Science, pages 364--380. Springer-Verlag, 2006. Software available at http://jtlv.sourceforge.net/.

Digital Library

[18]

S. J. Russell and P. Norvig. Artificial Intelligence: A Modern Approach. Pearson Education, 2003.

Digital Library

[19]

P. Tabuada and G. J. Pappas. Linear time logic control of linear systems. IEEE Transaction on Automatic Control, 51(12):1862--1877, 2006.

[20]

H. Tanner and G. J. Pappas. Simulation relations for discrete-time linear systems. In Proc. of the IFAC World Congress on Automatic Control, pages 1302--1307, 2002.

[21]

T. Wongpiromsarn and R. M. Murray. Distributed mission and contingency management for the DARPA urban challenge. In International Workshop on Intelligent Vehicle Control Systems (IVCS), 2008.

[22]

T. Wongpiromsarn, U. Topcu, and R. M. Murray. Receding horizon temporal logic planning for dynamical systems. In Proc. of IEEE Conference on Decision and Control, Dec. 2009.

Cited By

Singh SHuang ZSrinivasan AGutow GVundurthy BChoset H(2024)Hierarchical Planning for Long-Horizon Multi-Agent Collective Construction2024 IEEE International Conference on Robotics and Automation (ICRA)10.1109/ICRA57147.2024.10611496(9003-9009)Online publication date: 13-May-2024
https://doi.org/10.1109/ICRA57147.2024.10611496
Pacheck AJames SKonidaris GKress-Gazit H(2023)Automatic encoding and repair of reactive high-level tasks with learned abstract representationsThe International Journal of Robotics Research10.1177/0278364923116720742:4-5(263-288)Online publication date: 16-May-2023
https://doi.org/10.1177/02783649231167207
Cardona GKamale DVasile C(2023)Mixed Integer Linear Programming Approach for Control Synthesis with Weighted Signal Temporal LogicProceedings of the 26th ACM International Conference on Hybrid Systems: Computation and Control10.1145/3575870.3587120(1-12)Online publication date: 9-May-2023
https://dl.acm.org/doi/10.1145/3575870.3587120
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Index Terms

Receding horizon control for temporal logic specifications
1. Computing methodologies
  1. Artificial intelligence
    1. Control methods
      1. Computational control theory
    2. Planning and scheduling
2. Software and its engineering
  1. Software creation and management
    1. Designing software
    2. Software verification and validation
      1. Formal software verification
  2. Software organization and properties
    1. Software functional properties
      1. Formal methods

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cover image ACM Conferences

HSCC '10: Proceedings of the 13th ACM international conference on Hybrid systems: computation and control

April 2010

308 pages

ISBN:9781605589558

DOI:10.1145/1755952

General Chairs:
Karl Henrik Johansson
KTH, Sweden
,
Wang Yi
Uppsala University, Sweden

Copyright © 2010 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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SIGBED: ACM Special Interest Group on Embedded Systems

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New York, NY, United States

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Published: 12 April 2010

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HSCC '10

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HSCC '10: The 13th ACM International Conference on Hybrid Systems: Computation and Control

April 12 - 15, 2010

Stockholm, Sweden

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Overall Acceptance Rate 153 of 373 submissions, 41%

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https://doi.org/10.1109/ICRA57147.2024.10611496
Pacheck AJames SKonidaris GKress-Gazit H(2023)Automatic encoding and repair of reactive high-level tasks with learned abstract representationsThe International Journal of Robotics Research10.1177/0278364923116720742:4-5(263-288)Online publication date: 16-May-2023
https://doi.org/10.1177/02783649231167207
Cardona GKamale DVasile C(2023)Mixed Integer Linear Programming Approach for Control Synthesis with Weighted Signal Temporal LogicProceedings of the 26th ACM International Conference on Hybrid Systems: Computation and Control10.1145/3575870.3587120(1-12)Online publication date: 9-May-2023
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