Understand
In this paper we develop a Model Predictive Path Integral (MPPI) control algorithm based on a generalized importance sampling scheme and perform parallel optimization via sampling using a Graphics Processing Unit (GPU).
- The proposed generalized importance sampling scheme allows for changes in the drift and diffusion terms of stochastic diffusion processes and plays a significant role in the performance of the model predictive control algorithm.
- We compare the proposed algorithm in simulation with a model predictive control version of differential dynamic programming.
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Differential dynamic programming
D. H. Jacobson and D. Q. Mayne · 1970
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Stochastic Differential Equations And Applications
A. Friedman · 1975
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Brownian Motion and Stochastic Calculus (Graduate Texts in Mathematics)
I. Karatzas and S. E. Shreve · 1991
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R. F. Stengel · 1994
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Linear theory for control of nonlinear stochastic systems
H. J. Kappen · 2005
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A generalized iterative lqg method for locally-optimal feedback control of constrained nonlinear stochastic systems
E. Todorov and W. Li · 2005
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Controlled Markov processes and viscosity solutions
W. H. Fleming and H. M. Soner · 2006
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