Sampling-based motion planning with deterministic mu-calculus specifications
Author(s)Karaman, Sertac; Frazzoli, Emilio
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Sampling-based motion planning with deterministic μ-calculus specifications
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In this paper, we propose algorithms for the on-line 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 mu-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.
DepartmentMassachusetts 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
Proceedings of the 48th IEEE Conference on Decision and Control, 2009 held jointly with the 2009 28th Chinese Control Conference. CDC/CCC 2009
Institute of Electrical and Electronics Engineers
Karaman, S., and E. Frazzoli. “Sampling-based motion planning with deterministic μ-calculus specifications.” Decision and Control, 2009 held jointly with the 2009 28th Chinese Control Conference. CDC/CCC 2009. Proceedings of the 48th IEEE Conference on. 2009. 2222-2229. ©2010 Institute of Electrical and Electronics Engineers.
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INSPEC Accession Number: 11148960