Motion Planning Under Uncertainty Using Differential Dynamic Programming in Belief Space

Abstract

We present an approach to motion planning under motion and sensing uncertainty, formally described as a continuous partially-observable Markov decision process (POMDP). Our approach is designed for non-linear dynamics and observation models, and follows the general POMDP solution framework in which we represent beliefs by Gaussian distributions, approximate… (More)
DOI: 10.1007/978-3-319-29363-9_27

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@inproceedings{Berg2011MotionPU, title={Motion Planning Under Uncertainty Using Differential Dynamic Programming in Belief Space}, author={Jur P. van den Berg and Sachin Patil and Ron Alterovitz}, booktitle={ISRR}, year={2011} }