Abstract
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.
Highlights
Nowadays, mobile robots are able to efficiently map indoor and outdoor environments
We propose a modeling → conceptualization → evaluation process based on a 3D scanning and a Qualitative Spatio-Temporal Representation and Reasoning (QSTRR) framework capable of modeling the environment in the sense of generating a qualitative representation
The main goal of this work is to develop an assistance system for supporting designers in decision making based on the Qualitative Spatial Representation and Reasoning (QSRR) [12]
Summary
Mobile robots are able to efficiently map indoor and outdoor environments. They experience no fatigue and many state of the art systems are robust enough to perform this task autonomously. The robot is able to compare current 3D information with the reference model to locate new objects. These objects are considered as objects of potential interest OPI that are confirmed by a classification procedure. Accurate 3D models are used in spatial design support. The work in this paper aims at improving the last three steps. Our goal is to propose a solution to end-users that allows easier improvement and redesigning of already
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
