Please use this identifier to cite or link to this item:
|Title:||A penalized nonparametric method for nonlinear constrained optimization based on noisy data|
Garcia, Nancy L.
Zambom, Adriano Z.
|Abstract:||The objective of this study is to find a smooth function joining two points A and B with minimum length constrained to avoid fixed subsets. A penalized nonparametric method of finding the best path is proposed. The method is generalized to the situation where stochastic measurement errors are present. In this case, the proposed estimator is consistent, in the sense that as the number of observations increases the stochastic trajectory converges to the deterministic one. Two applications are immediate, searching the optimal path for an autonomous vehicle while avoiding all fixed obstacles between two points and flight planning to avoid threat or turbulence zones.|
The objective of this study is to find a smooth function joining two points A and B with minimum length constrained to avoid fixed subsets. A penalized nonparametric method of finding the best path is proposed. The method is generalized to the situation w
Spline, Teoria do
Ajuste de curva
Otimização com restrições
Estatística não paramétrica
|Citation:||Computational Optimization And Applications. Springer, v. 45, n. 3, n. 521, n. 541, 2010.|
|Appears in Collections:||IMECC - Artigos e Outros Documentos|
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.