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The DOI matches its Crossref record; 12 of the 12 references it cites were found in a registry or an index.

Synthesis and stabilization of complex behaviors through online trajectory optimization

Tassa, Yuval, Erez, Tom, Todorov, Emanuel·2012·2012 IEEE/RSJ International Conference on Intelligent Robots and Systems

Abstract

We present an online trajectory optimization method and software platform applicable to complex humanoid robots performing challenging tasks such as getting up from an arbitrary pose on the ground and recovering from large disturbances using dexterous acrobatic maneuvers. The resulting behaviors, illustrated in the attached video, are computed only 7 × slower than real time, on a standard PC. The video also shows results on the acrobot problem, planar swimming and one-legged hopping. These simpler problems can already be solved in real time, without pre-computing anything.

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Metadata

Authors
Tassa, Y., Erez, T., & Todorov, E.
Venue
2012 IEEE/RSJ International Conference on Intelligent Robots and Systems
Publisher
IEEE
Published
2012-10
Pages
4906-4913
OpenAlex
W2087617385
Cited by
744
References
12
FWCI
40.63
Type
conference paper
Language
en
Open access
closed

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CoChat. (2026). Citation check: Synthesis and stabilization of complex behaviors through online trajectory optimization. https://app.cochat.ai/papers/10.1109/iros.2012.6386025
The paper
Tassa, Y., Erez, T., & Todorov, E. (2012). Synthesis and stabilization of complex behaviors through online trajectory optimization. 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems. https://doi.org/10.1109/iros.2012.6386025

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.