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Stereo vision based automated grasp planning

机译:基于立体视觉的自动化掌握计划

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The Department of Energy has a need for treating existing nuclear waste. Hazardous waste stored in old warehouses needs to be sorted and treated to meet environmental regulations. Lawrence Livermore National Laboratory is currently experimenting with automated manipulations of unknown objects for sorting, treating, and detailed inspection. To accomplish these tasks, three existing technologies were expanded to meet the increasing requirements. First, a binocular vision range sensor was combined with a surface modeling system to make virtual images of unknown objects. Then, using the surface model information, stable grasp of the unknown shaped objects were planned algorithmically utilizing a limited set of robotic grippers. This paper is an expansion of previous work and will discuss the grasp planning algorithm.

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