Published November 2012 | Version public
Journal Article

Receding Horizon Temporal Logic Planning

Abstract

We present a methodology for automatic synthesis of embedded control software that incorporates a class of linear temporal logic (LTL) specifications sufficient to describe a wide range of properties including safety, stability, progress, obligation, response and guarantee. To alleviate the associated computational complexity of LTL synthesis, we propose a receding horizon framework that effectively reduces the synthesis problem into a set of smaller problems. The proposed control structure consists of a goal generator, a trajectory planner, and a continuous controller. The goal generator reduces the trajectory generation problem into 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 with respect to its specification regardless of the environment in which the system operates. In addition, we present a response mechanism to handle failures that may occur due to a mismatch between the actual system and its model. The effectiveness of the proposed technique is demonstrated through an example of an autonomous vehicle navigating an urban environment. This example also illustrates that the system is not only robust with respect to exogenous disturbances but is also capable of properly handling violation of the environment assumption that is explicitly stated as part of the system specification.

Additional Information

© 2012 IEEE. Manuscript received April 03, 2010; revised January 02, 2011; accepted October 11, 2011. Date of publication April 26, 2012; date of current version October 24, 2012. This work was supported in part by AFOSR under MURI grant FA9550-06-1-0303 and the Boeing Corporation. Recommended by Associate Editor J. Cortes. The authors gratefully acknowledge H. Kress-Gazit and Y. Sa'ar for inspiring discussions.

Additional details

Identifiers

Eprint ID
36081
DOI
10.1109/TAC.2012.2195811
Resolver ID
CaltechAUTHORS:20121220-142113975

Related works

Funding

Air Force Office of Scientific Research (AFOSR) Multidisciplinary University Research Initiative (MURI)
FA9550-06-1-0303
Boeing Corporation

Dates

Created
2013-02-12
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Updated
2021-11-09
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13100508