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Graspit! A versatile simulator for robotic grasping
TLDR
The different types of world elements and the general robot definition are discussed and the robot library is presented, and the grip analysis and visualization method were presented.
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A survey of sensor planning in computer vision
TLDR
A survey of research in the area of vision sensor planning is presented, and a brief description of representative sensing strategies for the tasks of object recognition and scene reconstruction are presented.
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Hand Posture Subspaces for Dexterous Robotic Grasping
TLDR
An on-line grasp planner that allows a human operator to perform dexterous grasping tasks using an artificial hand in a hand posture subspace of highly reduced dimensionality is presented.
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Automatic grasp planning using shape primitives
TLDR
This paper aims to simplify automatic grasp planning for robotic hands by modeling an object as a set of shape primitives, such as spheres, cylinders, cones and boxes, to generate aSet of grasp starting positions and pregrasp shapes that can then be tested on the object model.
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Shape completion enabled robotic grasping
TLDR
This work provides an architecture to enable robotic grasp planning via shape completion through the use of a 3D convolutional neural network trained on a new open source dataset of over 440,000 3D exemplars captured from varying viewpoints.
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The Columbia grasp database
TLDR
This work shows how to automate the construction of a database consisting of several hands, thousands of objects, and hundreds of thousands of grasps, and demonstrates a novel grasp planning algorithm that exploits geometric similarity between a 3D model and the objects in the database to synthesize form closuregrasps.
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Examples of 3D grasp quality computations
TLDR
A unique grasp analysis system that, when given a 3D object, hand, and pose for the hand, can accurately determine the types of contacts that will occur between the links of the hand and the object, and compute two measures of quality for the grasp.
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Dimensionality reduction for hand-independent dexterous robotic grasping
TLDR
This paper builds upon recent advances in neuroscience research which have shown that control of the human hand during grasping is dominated by movement in a configuration space of highly reduced dimensionality and builds a comprehensive grasp planner that can be used on a large variety of robotic hands under various constraints.
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Pose error robust grasping from contact wrench space metrics
TLDR
This work examines a large number of grasps from the Columbia Grasp Database for the Barrett hand and finds that in most cases the grasp with the most robust force closure with respect to pose error for a particular object is not the grasped with the highest epsilon quality.
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Automated tracking and grasping of a moving object with a robotic hand-eye system
An attempt to achieve a high level of interaction between a real-time vision system capable of tracking moving objects in 3-D and a robot arm with gripper that can be used to pick up a moving object…
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