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Cited by 409

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

LQR-trees: Feedback Motion Planning via Sums-of-Squares Verification

Tedrake, Russ, Manchester, Ian R., Tobenkin, Mark, Roberts, John W.·2010·The International Journal of Robotics Research

Abstract

Advances in the direct computation of Lyapunov functions using convex optimization make it possible to efficiently evaluate regions of attraction for smooth non-linear systems. Here we present a feedback motion-planning algorithm which uses rigorously computed stability regions to build a sparse tree of LQR-stabilized trajectories. The region of attraction of this non-linear feedback policy “probabilistically covers” the entire controllable subset of state space, verifying that all initial conditions that are capable of reaching the goal will reach the goal. We numerically investigate the properties of this systematic non-linear feedback design algorithm on simple non-linear systems, prove the property of probabilistic coverage, and discuss extensions and implementation details of the basic algorithm.

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Metadata

Authors
Tedrake, R., Manchester, I. R., Tobenkin, M., & Roberts, J. W.
Venue
The International Journal of Robotics Research
Published
2010-04-22
Volume
29
Issue
8
Pages
1038-1052
ISSN
  • 0278-3649 (ISSN-L)
  • 1741-3176
OpenAlex
W2100538121
Cited by
409
References
1
FWCI
19.53
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: LQR-trees: Feedback Motion Planning via Sums-of-Squares Verification. https://app.cochat.ai/papers/10.1177/0278364910369189
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Tedrake, R., Manchester, I. R., Tobenkin, M., & Roberts, J. W. (2010). LQR-trees: Feedback Motion Planning via Sums-of-Squares Verification. The International Journal of Robotics Research. https://doi.org/10.1177/0278364910369189

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