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Silhouette-Based Isolated Object Recognition through Curvature Scale Space
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Ein 3D Weltmodell zur teilaktiven Positionsverfolgung in komplexen dynamischen Umgebungen
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Quality Enhancement of Reconstructed 3D Models Using Coplanarity and Constraints
Proceedings of the 24th DAGM Symposium on Pattern Recognition
Artificial Intelligence: A Modern Approach
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A scene analysis system for the generation of 3-D models
NRC '97 Proceedings of the International Conference on Recent Advances in 3-D Digital Imaging and Modeling
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Knowledge Representation and Reasoning
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Introduction to Autonomous Mobile Robots
An Efficient Extension to Elevation Maps for Outdoor Terrain Mapping and Loop Closing
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Appearance-Based SLAM for Mobile Robots
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ICCCI'11 Proceedings of the Third international conference on Computational collective intelligence: technologies and applications - Volume Part II
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International Journal of Robotics Research
Model-based object recognition from 3D laser data
KI'11 Proceedings of the 34th Annual German conference on Advances in artificial intelligence
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Intelligent Service Robotics
Online semantic mapping of urban environments
SC'12 Proceedings of the 2012 international conference on Spatial Cognition VIII
DHM'13 Proceedings of the 4th international conference on Digital Human Modeling and Applications in Health, Safety, Ergonomics, and Risk Management: human body modeling and ergonomics - Volume Part II
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ICVS'13 Proceedings of the 9th international conference on Computer Vision Systems
Three-dimensional point cloud plane segmentation in both structured and unstructured environments
Robotics and Autonomous Systems
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Real-time plane segmentation using RGB-D cameras
Robot Soccer World Cup XV
Multimedia access to mobile environments using indoor semantic maps
Multimedia Tools and Applications
Contextual object category recognition for RGB-D scene labeling
Robotics and Autonomous Systems
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Intelligent autonomous action in ordinary environments calls for maps. 3D geometry is generally required for avoiding collision with complex obstacles and to self-localize in six degrees of freedom (6 DoF) (x, y, z positions, roll, yaw, and pitch angles). Meaning, in addition to geometry, becomes inevitable if the robot is supposed to interact with its environment in a goal-directed way. A semantic stance enables the robot to reason about objects; it helps disambiguate or round off sensor data; and the robot knowledge becomes reviewable and communicable. The paper describes an approach and an integrated robot system for semantic mapping. The prime sensor is a 3D laser scanner. Individual scans are registered into a coherent 3D geometry map by 6D SLAM. Coarse scene features (e.g., walls, floors in a building) are determined by semantic labeling. More delicate objects are then detected by a trained classifier and localized. In the end, the semantic maps can be visualized for human inspection. We sketch the overall architecture of the approach, explain the respective steps and their underlying algorithms, give examples based on a working robot implementation, and discuss the findings.