Using Visual Features to Predict Successful Grasp Parameters
نویسنده
چکیده
Visual features act as an important part for hand pre-shaping during human grasp. This paper focuses on using visual features in an image to predict successful grasp types, which can be used in the robot grasp manipulation. The following questions are discussed: First, how to recognize different shapes in a given image. Second, how to train the system using image-grasp pairs. Third, evaluate the result of the learning process using testing sets. Also, future work is introduced at the end of the paper. Index Terms – Visual features; Random edgel constellations; Grasp parameters vote.
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