2006
DOI: 10.3182/20060912-3-de-2911.00086
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A Framework for Grasp Simulation and Control in Domestic Environments

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Cited by 4 publications
(4 citation statements)
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“…In this paper, a weighted sum of the contact forces, finger position difference (stability), off-set (centering), and finger spread is controlled (see Fig. 3 and [29] for more detail). The transform T used in this paper is…”
Section: Grasp Controlmentioning
confidence: 99%
“…In this paper, a weighted sum of the contact forces, finger position difference (stability), off-set (centering), and finger spread is controlled (see Fig. 3 and [29] for more detail). The transform T used in this paper is…”
Section: Grasp Controlmentioning
confidence: 99%
“…However, this can be considered as a separate problem and is outside the scope of this study. Another way of improving performance is to add a more advanced controller, such as the one presented in [22]. Here, the estimated pose combined with tactile sensing is used as feedback to adjust the forces applied at the finger joints.…”
Section: Grasp Controllersmentioning
confidence: 99%
“…In our work, we do not consider the control paradigm but we correct grasps based on prior experience. The work of [12] did not consider the success of a grasp before executing the controller.…”
Section: Related Workmentioning
confidence: 99%
“…[11] used a programming by demonstration approach where a robot relies on human-to-robot grasp mapping to learn most likely hand preshapes for specific objects. Starting from the inferred preshape, a force controller that relied on joint angles and tactile sensing [12] was selected to handle position and orientation uncertainty. A grasp was chosen via control laws and experience was only used to select the hand preshapes for the given object.…”
Section: Related Workmentioning
confidence: 99%