Scaling up Gaussian Belief Space Planning Through Covariance-Free Trajectory Optimization and Automatic Differentiation-Reference-Cited by-同舟云学术

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Scaling up Gaussian Belief Space Planning Through Covariance-Free Trajectory Optimization and Automatic Differentiation

Published:2015 Issue: Volume: Page:515-533
ISSN:1610-7438
Container-title:Springer Tracts in Advanced Robotics
language:
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Author:

Patil Sachin,Kahn Gregory,Laskey Michael,Schulman John,Goldberg Ken,Abbeel Pieter

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-319-16595-0_30

Reference38 articles.

1. Agha-mohammadi, A., Chakravorty, S., Amato, N.M.: FIRM: sampling-based feedback motion planning under motion uncertainty and imperfect measurements. Int. J. Robot. Res. 33(2), 268–304 (2014)

2. Andersson, J., Åkesson, J., Diehl, M.: CasADi: a symbolic package for automatic differentiation and optimal control. In: Recent Advances in Algorithmic Differentiation, pp. 297–307. Springer (2012)

3. Bergstra, J.: Theano: a CPU and GPU math expression compiler. http://deeplearning.net/software/theano/ (2011)

4. Bertsekas, D.: Dynamic Programming and Optimal Control. Athena Scientific (2001)

5. Betts, J.T.: Practical Methods for Optimal Control and Estimation Using Nonlinear Programming. SIAM, Philadelphia (2010)

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