Sampling-based motion planning with deterministic u-calculus specifications
Author(s)Karaman, Sertac; Frazzoli, Emilio
MetadataShow full item record
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.
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 CDC/CCC 2009
Institute of Electrical and Electronics Engineers
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.
Author's final manuscript
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