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Iker Aguinaga
Researcher at University of Navarra
Publications - 21
Citations - 476
Iker Aguinaga is an academic researcher from University of Navarra. The author has contributed to research in topics: Augmented reality & Finite element method. The author has an hindex of 11, co-authored 21 publications receiving 346 citations. Previous affiliations of Iker Aguinaga include Centro de Estudios e Investigaciones Técnicas de Gipuzkoa & Tecnun.
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Journal ArticleDOI
Parallel RRT-based path planning for selective disassembly planning
TL;DR: This paper presents a modification of the rapid-growing random tree-based algorithm (RRT) that addresses the main differences between both the disassembly path-planning problem and the general path- planners, such as the lack of a target configuration.
Journal ArticleDOI
Direct Sparse Mapping
TL;DR: Direct sparse mapping is presented, a full monocular visual simultaneous localization and mapping (SLAM) based on PBA, yielding the most accurate results up to date on EuRoC for a direct method.
Journal ArticleDOI
Cubical Mass-Spring Model Design Based on a Tensile Deformation Test and Nonlinear Material Model
TL;DR: The obtained results show that MSMs can be designed to realistically model the behavior of hyperelastic materials such as soft tissues and can become an interesting alternative to other approaches such as nonlinear FEM.
Proceedings ArticleDOI
Providing guidance for maintenance operations using automatic markerless Augmented Reality system
TL;DR: A new real-time Augmented Reality based tool to help in disassembly for maintenance operations that provides workers with augmented instructions to perform maintenance tasks more efficiently.
Journal ArticleDOI
A framework for augmented reality guidance in industry
Jon Zubizarreta,Jon Zubizarreta,Iker Aguinaga,Iker Aguinaga,Aiert Amundarain,Aiert Amundarain +5 more
TL;DR: A complete framework to generate and present virtual and augmented information, including the tools required for the development of new contents, is presented, called ARgitu, and a new monocular method for 3D non-Lambertian object recognition in arbitrary environments is proposed.