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members:sturmju:research:bodyschema [2011/07/12 11:12] sturmju |
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| + | ====== Body Schema Learning ====== | ||
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| + | Kinematic models are widely used in robotics to describe the mechanism | ||
| + | of a robot. For example, the kinematic model of a manipulation robot | ||
| + | is typically specified by the position of its joints, and the size and orientation of its links. Kinematic models are usually derived | ||
| + | analytically by a robot engineer and thus rely heavily on prior | ||
| + | knowledge about the geometry of the robot. When such a model is | ||
| + | applied to a real robot, its parameters have to be carefully | ||
| + | calibrated to ensure a high accuracy, for example, | ||
| + | using expensive calibration systems at the robot manufacturer' | ||
| + | As robotic systems become more versatile and are increasingly | ||
| + | delivered in completely reconfigurable ways, there is a growing demand | ||
| + | for techniques to learn kinematic models automatically. Ideally, such | ||
| + | techniques would neither require human intervention nor costly | ||
| + | calibration equipment. This capability does not only facilitate the | ||
| + | deployment and calibration of new robotic systems but also enables | ||
| + | robots to autonomously adapt their models when the kinematics change, | ||
| + | for example, as a result of hardware failures or material | ||
| + | fatigue. Furthermore, | ||
| + | robot to include a tool dynamically in its kinematic model. | ||
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| + | < | ||
| + | <iframe width=" | ||
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| + | </ | ||
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| + | ====== Related Publications ====== | ||
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| + | < | ||
| + | < | ||
| + | < | ||
| + | </ | ||
