A topology-guided path integral approach for stochastic optimal control

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This work presents an efficient method to solve a class of continuous-time, continuous-space stochastic optimal control problems of robot motion in a cluttered environment. The method builds upon a path integral representation of the stochastic optimal control problem that allows computation of the optimal solution through sampling and estimation process. As this sampling process often leads to a local minimum especially when the state space is highly non-convex due to the obstacle field, we present an efficient method to alleviate this issue by devising a proposed topological motion planning algorithm. Combined with a receding-horizon scheme in execution of the optimal control solution, the proposed method can generate a dynamically feasible and collision-free trajectory while reducing concern about local optima. Illustrative numerical examples are presented to demonstrate the applicability and validity of the proposed approach.
Publisher
IEEE Robotics and Automation Society
Issue Date
2016-05
Language
English
Citation

2016 IEEE International Conference on Robotics and Automation, ICRA 2016, pp.4605 - 4612

ISSN
1050-4729
DOI
10.1109/ICRA.2016.7487662
URI
http://hdl.handle.net/10203/313206
Appears in Collection
AE-Conference Papers(학술회의논문)
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