Christian Bard

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This paper deals with the automation of dextrous grasping in a partly known environment using a stereo vision system and a multiingered hand mounted on a robot arm. EEective grasping requires a combination of sensing and planning capabilities: sensing to construct a well-adapted model of the situation and to guide the execution of the task, and planning to(More)
Planning robust grasping operations involving a dex-trous robotics hand and an object located in a three dimensional workspace requires to combine two main types of techniques: a geometric based reasoning aimed at producing a grasping strategy (preshape of the hand, grasping parameters, type of motion to execute), and a physical analysis of the object/hand(More)
| This paper addresses motion planning for robots subjected to strong physical interaction constraints. More precisely, we will show how to solve two particular instances of this general problem: the case of a rover moving on a hilly three dimensional terrain, and the case of a dextrous hand executing a grasping operation. In addition to the high dimension(More)
This paper deals with the automation of dextrous grasping in a partly known environment using a stereo vision system and a multiingered hand mounted on a robot arm. EEective grasping requires a combination of sensing and planning capabilities: sensing to construct a well-adapted model of the situation and to guide the execution of the task, and planning to(More)
The study of human grasping has shown that during the reaching phase of grasping, the hand preshapes in order to prepare the 'shape matching' with the object. A preshape represents a class of configurations, among which, one is executed by adjusting the fingers against the object. Preshaping is guided by visual data providing with the object description.(More)
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