Mv
M.F. van Schendel
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Topometric Maps of Indoor Environments
Extraction, matching and fusion
The merging of multiple partial maps of indoor environments created
by teams of human or robot agents into a single global map is a key problem
that, when solved, can improve mapping speed and quality. Existing map
merging approaches generally depend on external signals which are not available indoors or only use the geometric properties of an environment. Inspired by the human understanding of environments in relationship to their context we propose a map merging system that extracts and uses topometric maps, a map representation containing both the geometric and topological characteristics of an environments, to solve the map merging problem in indoor spaces. In this research we demonstrate an intuitive approach to extracting topometric maps of 3D, multi-floor, indoor environments and use both the topological and geometric characteristics contained in the topometric maps to perform context-aware map matching and fusion. ...
by teams of human or robot agents into a single global map is a key problem
that, when solved, can improve mapping speed and quality. Existing map
merging approaches generally depend on external signals which are not available indoors or only use the geometric properties of an environment. Inspired by the human understanding of environments in relationship to their context we propose a map merging system that extracts and uses topometric maps, a map representation containing both the geometric and topological characteristics of an environments, to solve the map merging problem in indoor spaces. In this research we demonstrate an intuitive approach to extracting topometric maps of 3D, multi-floor, indoor environments and use both the topological and geometric characteristics contained in the topometric maps to perform context-aware map matching and fusion. ...
The merging of multiple partial maps of indoor environments created
by teams of human or robot agents into a single global map is a key problem
that, when solved, can improve mapping speed and quality. Existing map
merging approaches generally depend on external signals which are not available indoors or only use the geometric properties of an environment. Inspired by the human understanding of environments in relationship to their context we propose a map merging system that extracts and uses topometric maps, a map representation containing both the geometric and topological characteristics of an environments, to solve the map merging problem in indoor spaces. In this research we demonstrate an intuitive approach to extracting topometric maps of 3D, multi-floor, indoor environments and use both the topological and geometric characteristics contained in the topometric maps to perform context-aware map matching and fusion.
by teams of human or robot agents into a single global map is a key problem
that, when solved, can improve mapping speed and quality. Existing map
merging approaches generally depend on external signals which are not available indoors or only use the geometric properties of an environment. Inspired by the human understanding of environments in relationship to their context we propose a map merging system that extracts and uses topometric maps, a map representation containing both the geometric and topological characteristics of an environments, to solve the map merging problem in indoor spaces. In this research we demonstrate an intuitive approach to extracting topometric maps of 3D, multi-floor, indoor environments and use both the topological and geometric characteristics contained in the topometric maps to perform context-aware map matching and fusion.
Student report
(2020)
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Camille Morlighem, Charalampos Chatzidiakos, Jos Feenstra, Max van Schendel, Robin Hurkmans, E. Verbree, R.L. Voûte
The Deployment of Indoor Point Clouds for Firefighting Strategy project was realised as a Synthesis Project of the Geomatics Master Programme of the Built Environment Faculty at the Technical University of Delft. This project was executed by a team of five Master students in collaboration with the Dutch response team collective Veiligheidsregio Rotterdam-Rijnmond. The objective of this project is to develop an information system that makes use of indoor data to support tactical decision-making during fire emergency responses. The main challenge that response teams are facing when they develop deployment plans is the lack of appropriate information about indoor spaces. As a result, response teams may end up relying on inaccurate assumptions which can lead to dangerous situations. New technologies such as SLAM devices and augmented reality displays, combined with processing techniques, can be used to supply them with the information needed to make the right choices. The result of this project is a prototypical information system containing an interactive, 3D environment that can receive updates, merge data from different data sources, and accommodate mixed reality information sharing in real-time.
...
The Deployment of Indoor Point Clouds for Firefighting Strategy project was realised as a Synthesis Project of the Geomatics Master Programme of the Built Environment Faculty at the Technical University of Delft. This project was executed by a team of five Master students in collaboration with the Dutch response team collective Veiligheidsregio Rotterdam-Rijnmond. The objective of this project is to develop an information system that makes use of indoor data to support tactical decision-making during fire emergency responses. The main challenge that response teams are facing when they develop deployment plans is the lack of appropriate information about indoor spaces. As a result, response teams may end up relying on inaccurate assumptions which can lead to dangerous situations. New technologies such as SLAM devices and augmented reality displays, combined with processing techniques, can be used to supply them with the information needed to make the right choices. The result of this project is a prototypical information system containing an interactive, 3D environment that can receive updates, merge data from different data sources, and accommodate mixed reality information sharing in real-time.