Sampling-based motion planning with deterministic u-calculus specifications
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Frazzoli_SamplingBased.pdf
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Author(s)
Karaman, Sertac
Frazzoli, Emilio
Date Issued
January 2010
Journal
Proceedings of the 48th IEEE Conference on CDC/CCC 2009
Publisher
Institute of Electrical and Electronics Engineers
Citation
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.
Version
Author's final manuscript
Abstract
In this paper, we propose algorithms for the online
computation of control programs for dynamical systems
that provably satisfy a class of temporal logic specifications.
Such specifications have recently been proposed in the literature
as a powerful tool to synthesize provably correct
control programs, for example for embedded systems and
robotic applications. The proposed algorithms, generalizing
state-of-the-art algorithms for point-to-point motion planning,
incrementally build finite transition systems representing a
discrete subset of dynamically feasible trajectories. At each
iteration, local -calculus model-checking methods are used
to establish whether the current transition system satisfies
the specifications. Efficient sampling strategies are presented,
ensuring the probabilistic completeness of the algorithms. We
demonstrate the effectiveness of the proposed approach on
simulation examples.
Subjects
temporal logic specification
sampling based motion planning
provably correct control program
probabilistic completeness
point-to-point motion planning
finite transition system
iteration method
dynamically feasible trajectory
dynamical system
control program online computation
MIT Department
Massachusetts Institute of Technology. Department of Aeronautics and Astronautics
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Massachusetts Institute of Technology. Laboratory for Information and Decision Systems
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Attribution-Noncommercial-Share Alike 3.0 Unported
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DOI of Published Version
https://doi.org/10.1109/CDC.2009.5400278
