2006
DOI: 10.1007/11780519_30
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3D Mapping with Semantic Knowledge

Abstract: Abstract.A basic task of rescue robot systems is mapping of the environment. Localizing injured persons, guiding rescue workers and excavation equipment requires a precise 3D map of the environment. This paper presents a new 3D laser range finder and novel scan matching method for the robot Kurt3D [9]. Compared to previous machinery [12], the apex angle is enlarged to 360 • . The matching is based on semantic information. Surface attributes are extracted and incorporated in a forest of search trees in order to… Show more

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Cited by 59 publications
(52 citation statements)
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“…This means that each point p i represents the distance on the three defined coordinate axes from the acquisition viewpoint to the surface that the point has been sampled on. Though there are many ways of measuring distances and converting them to 3D points, in the context of mobile robotic applications [Nue09], the two most used approaches are:…”
Section: Data Acquisitionmentioning
confidence: 99%
“…This means that each point p i represents the distance on the three defined coordinate axes from the acquisition viewpoint to the surface that the point has been sampled on. Though there are many ways of measuring distances and converting them to 3D points, in the context of mobile robotic applications [Nue09], the two most used approaches are:…”
Section: Data Acquisitionmentioning
confidence: 99%
“…The main advantage of using 3-D models of environments is that they are more descriptive and have richer information content than 2-D models in terms of the features extracted from the environments, resulting in less ambiguity in distinguishing features [4]. 3-D models are used in fields varying from robot motion planning and navigation [3,5,6,7], art and architecture [8,9,10,11,12] to industry/urban planning, water management, and forestry documentation [13,14,15]. 3-D models can be obtained using a variety of sensors measuring range or intensity.…”
Section: -D Modeling Techniques Allow Describing Environments Includmentioning
confidence: 99%
“…Such classifiers have been used previously Mozos et al (2005) to classify indoor places. Later, several approaches were proposed in literature to improve performance by taking advantage of object recognition (Nuchter et al, 2005) and probabilistic environment models (Mozos et al, 2007). A GHMM consists of a discrete-time and discrete-space Markov process that contains some hidden parameters and emits observable outputs (Rabiner, 1989).…”
Section: State-of-art Algorithmsmentioning
confidence: 99%