Vision and motion planning for a mobile robot under uncertainty
International Journal of Robotics Research
Image retrieval using efficient local-area matching
Machine Vision and Applications
Sensor planning for 3D object search
Computer Vision and Image Understanding
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Intelligent and Efficient Strategy for Unstructured Environment Sensing Using Mobile Robot Agents
Journal of Intelligent and Robotic Systems
Cognitive maps for mobile robots-an object based approach
Robotics and Autonomous Systems
Robotics and Autonomous Systems
Object search using object co-occurrence relations derived from web content mining
Intelligent Service Robotics
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Mapping is an activity of making a useful description of an environment. Not only geometric information such as free space but also object placements are important if the map is used for human-robot communication. We call such a map making environment information summarization because how to summarize may change depending on the purpose of the map. Environment information summarization usually includes searching for specified objects in the environment. It is, therefore, crucial to make a good observation plan for efficient summarization. We develop an observation planning method which uses object appearance models for appropriately handling a trade-off between visual data quality and vision cost. Experimental results using a vision-based humanoid robot show the effectiveness of the proposed planning method.