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members:sturmju:research:tactile [2011/07/12 11:23] sturmju created |
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| + | ====== Tactile Sensing ====== | ||
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| + | In particular for robotic manipulation | ||
| + | tasks, tactile sensing provides another sensor modality that can | ||
| + | reveal relevant aspects about the object being manipulated, | ||
| + | example, to infer its identity, pose, and internal state. | ||
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| + | ==== Tactile object recognition using the bag-of-features approach ==== | ||
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| + | Our approach uses the bag-of-features model that we apply to object | ||
| + | classification based on tactile images. First, the robot generates a | ||
| + | suitable tactile feature vocabulary using unsupervised clustering from | ||
| + | real data. Second, it learns a set of feature models (a so-called | ||
| + | codebook that encodes the appearance of objects in form of | ||
| + | feature histograms. After training, a robot can use this codebook to | ||
| + | identify the grasped object. Since the objects that we | ||
| + | consider are typically larger than the sensor and consist of similar | ||
| + | parts, the robot may need multiple grasps at different | ||
| + | positions to uniquely identify an object. | ||
| + | number of required grasps, we apply a decision-theoretic framework that chooses | ||
| + | the grasping location in such a way that the expected entropy of the belief | ||
| + | distribution is minimized. | ||
| + | and household objects, we demonstrate that our approach enables a | ||
| + | manipulation robot to discriminate various objects only by touch. | ||
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| + | < | ||
| + | <iframe width=" | ||
| + | <iframe width=" | ||
| + | </ | ||
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| + | ==== Estimating the internal state of containers ==== | ||
| + | We investigated features that describe the | ||
| + | dynamics in the tactile response while the robot is | ||
| + | grasping or manipulating an object. As we showed, the dynamic | ||
| + | components of the tactile signal can be used to infer several aspects of the internal state | ||
| + | of an object. For example, these features allow a robot to | ||
| + | detect whether a grasped bottle contains liquid and whether its cap | ||
| + | has been properly closed. This information is highly relevant for | ||
| + | domestic robots that fulfill service tasks such as tidying up. | ||
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| + | ====== Related Publications ====== | ||
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| + | < | ||
| + | < | ||
| + | < | ||
| + | </ | ||
