Titlebook: Semantic 3D Object Maps for Everyday Robot Manipulation; Radu Bogdan Rusu Book 2013 Springer-Verlag Berlin Heidelberg 2013 3D Perception.M

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Static Scene Interpretationhe resultant model is accurate enough to use it in physics-based simulations, where doors of 3D containers can be opened based on their hinge position. The resultant map is represented as a hybrid concept and is comprised of hierarchically classified objects and triangular meshes used for collision avoidance in manipulation routines.

JOT

Surface and Object Class Learning points sampled from surfaces with similar geometrical properties together, or in some sense try to “classify the world”. Achieving the latter annotates sensed 3D points and geometric structures with higher level semantics and greatly simplifies research in the aforementioned topics (e.g. manipulation and grasping).

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Conclusionperceive and understand the semantic meanings of the objects present in the world. The key challenge in achieving that is being able to build semantic 3D perception architectures that can enable complex mobile manipulation scenarios.

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Organization

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Mapping System Architecturesut the “holy grail” of 3D mapping systems from a data interpretation point of view (in the context of our application scenario), the resultant system architecture would need to comprise a big list of geometric and learning steps, where the output of a step requires the input of another, and so on.