Using Orientation Information for Qualitative Spatial Reasoning
Proceedings of the International Conference GIS - From Space to Territory: Theories and Methods of Spatio-Temporal Reasoning on Theories and Methods of Spatio-Temporal Reasoning in Geographic Space
A Multiagent Approach to Qualitative Landmark-Based Navigation
Autonomous Robots
Efficient Graph-Based Image Segmentation
International Journal of Computer Vision
On Intelligence
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
A Comparison of Affine Region Detectors
International Journal of Computer Vision
Conceptual spatial representations for indoor mobile robots
Robotics and Autonomous Systems
Spatial Abstraction: Aspectualization, Coarsening, and Conceptual Classification
Proceedings of the international conference on Spatial Cognition VI: Learning, Reasoning, and Talking about Space
A qualitative approach to sensor data fusion for mobile robot navigation
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
Visual topological SLAM and global localization
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
A model for the qualitative description of images based on visual and spatial features
Computer Vision and Image Understanding
From Sensors to Human Spatial Concepts: An Annotated Data Set
IEEE Transactions on Robotics
Robust data fusion with occupancy grid
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
A Fuzzy Qualitative Framework for Connecting Robot Qualitative and Quantitative Representations
IEEE Transactions on Fuzzy Systems
Multi-granularity and metric spatial reasoning
Expert Systems with Applications: An International Journal
Hi-index | 0.10 |
Patterns of qualitative concepts are extracted from robot sensors in order to describe the shapes, colours, spatial orientations and topology situations of natural landmarks in the robot environment and also the distance to them. Those qualitative patterns are obtained at a low level sensor data processing and without using training on datasets or learning techniques. A qualitative distance integration approach is parametrized and applied to detect glass windows and mirrors. Corners and columns are detected by the laser sensor and described qualitatively as relevant landmarks. Images taken by the robot camera are described qualitatively for completing the description of the objects located in the robot environment. Experimentation carried out shows that the integration of the information provided enhances the robot perception.