Jonna Laaksonen

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This paper proposes a probabilistic framework for sensor-based grasping and describes how information about object attributes, such as position and orientation, can be updated using on-line sensor information gained during grasping. This allows learning about the target object even with a failed grasp, leading to replanning with improved performance at each(More)
In this paper, we present a novel probabilistic framework for grasping. In the framework, grasp and object attributes, on-line sensor information and the stability of a grasp are all considered through probabilistic models. We describe how sensor-based grasp planning can be formulated in a probabilistic framework and how information about object attributes(More)
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