Optymalizacja w zastosowaniu do planowania ruchu ściśle współpracujących robotów

pol Artykuł w języku polskim DOI:

Wojciech Szynkiewicz *, Jacek Błaszczyk **, Krzysztof Malinowski * * Instytut Automatyki i Informatyki Stosowanej Politechniki Warszawskiej ** Naukowa i Akademicka Sieć Komputerowa NASK

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Streszczenie

W artykule omówiono wykorzystanie zaawansowanych technik optymalizacji do rozwiązywania zadań planowania ścieżek ruchu dla ściśle współpracujących robotów. Zadanie planowania ścieżki jest formułowane jako problem minimalizacji warunkowej funkcjonału, a następnie jest sprowadzane do zadania programowania nieliniowego (NLP). Do numerycznego rozwiązania zadania NLP wykorzystuje się solwer IPOPT oparty na prymalno-dualnej metodzie punktu wewnętrznego dla zadań nieliniowych, będącej obecnie jedną z wiodących technik optymalizacji nieliniowej dla zadań wielkiej skali.

Optimization in motion planning for tightly cooperating robots

Abstract

Application of advanced optimization techniques to solve the path planning problem for tightly cooperating robots is discussed in this paper. The approach to path planning is formulated as a “quasi-dynamic” nonlinear optimization (NLP) problem with equality and inequality constraints in terms of the joint variables. The essence of the method is to find joint paths which satisfy the given constraints and minimize the proposed performance index. For numerical solution of the NLP problem the IPOPT solver is used, which implements a nonlinear primal-dual interior-point method one of the leading techniques for large-scale nonlinear optimization.

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