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Stochastic Extended LQR for Optimization-based Motion Planning Under Uncertainty
We introduce a novel optimization-based motion planner, Stochastic Extended LQR (SELQR), which computes a trajectory and associated linear control policy with the objective of minimizing the expected value of a user-defined cost function. SELQR applies to robotic systems that have stochastic non-lin...
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| Publicado no: | IEEE Trans Autom Sci Eng |
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| Main Authors: | , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
2016
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5287415/ https://ncbi.nlm.nih.gov/pubmed/28163662 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1109/TASE.2016.2517124 |
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