| Partner: Andreas Nüchter |
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Ostatnie publikacje
| 1. | Będkowski J., Majek K.♦, Majek P.♦, Musialik P.♦, Pełka M.♦, Nüchter A.♦, Intelligent Mobile System for Improving Spatial Design Support and Security Inside Buildings, Mobile Networks and Applications, ISSN: 1383-469X, DOI: 10.1007/s11036-015-0654-8, Vol.21, No.2, pp.313-326, 2016 Streszczenie: This paper concerns the an intelligent mobile application for spatial design support and security domain. Mobility has two aspects in our research: The first one is the usage of mobile robots for 3D mapping of urban areas and for performing some specific tasks. The second mobility aspect is related with a novel Software as a Service system that allows access to robotic functionalities and data over the Ethernet, thus we demonstrate the use of the novel NVIDIA GRID technology allowing to virtualize the graphic processing unit. We introduce Complex Shape Histogram, a core component of our artificial intelligence engine, used for classifying 3D point clouds with a Support Vector Machine. We use Complex Shape Histograms also for loop closing detection in the simultaneous localization and mapping algorithm. Our intelligent mobile system is built on top of the Qualitative Spatio-Temporal Representation and Reasoning framework. This framework defines an ontology and a semantic model, which are used for building the intelligent mobile user interfaces. We show experiments demonstrating advantages of our approach. In addition, we test our prototypes in the field after the end-user case studies demonstrating a relevant contribution for future intelligent mobile systems that merge mobile robots with novel data centers. Słowa kluczowe: Intelligent mobile system, 3D object recognition, Qualitative representation and reasoning, 3D mapping Afiliacje autorów:
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| 2. | Będkowski J.♦, Majek K.♦, Nüchter A.♦, General Purpose Computing on Graphics Processing Units for Robotic Applications, Journal of Software Engineering for Robotics, ISSN: 2035-3928, Vol.4, No.1, pp.23-33, 2013 Streszczenie: This paper deals with research related with the improvements of state of the art algorithms used in robotic applications based on parallel computation. The main goal is to decrease the computational complexity of 3D cloud of points processing in applications as: data filtering, normal vector estimation, data registration, and point feature histogram calculation. The presented results improve the efficiency of existing implementations with minimal lost of accuracy. The main contribution is a regular grid decomposition originally implemented for nearest neighborhood search. This data structure is the basis for all presented methods, it provides an efficient method for decreasing the time of computation. The results are compared with well-known robotic frameworks such as PCL and 3DTK. Afiliacje autorów:
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