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Vision and Robotics Seminar

ThursdayJan 18, 201812:15
Vision and Robotics SeminarRoom 1
Speaker:Sagie BenaimTitle:One-Sided Unsupervised Domain Mapping via Distance CorrelationsAbstract:opens in new windowin html    pdfopens in new window

In unsupervised domain mapping, the learner is given two unmatched datasets A and B. The goal is to learn a mapping G_AB that translates a sample in A to the analog sample in B. Recent approaches have shown that when learning simultaneously both G_AB and the inverse mapping G_BA, convincing mappings are obtained. In this work, we present a method of learning G_AB without learning G_BA. This is done by learning a mapping that maintains the distance between a pair of samples. Moreover, good mappings are obtained, even by maintaining the distance between different parts of the same sample before and after mapping. We present experimental results that the new method not only allows for one sided mapping learning, but also leads to preferable numerical results over the existing circularity-based constraint.

ThursdayJan 25, 201812:15
Vision and Robotics SeminarRoom 1
Speaker:Hallel Bunis Title:Caging Polygonal Objects Using Minimalistic Three-Finger HandsAbstract:opens in new windowin html    pdfopens in new window

Multi-finger caging offers a robust approach to object grasping. To securely grasp an object, the fingers are first placed in caging regions surrounding a desired immobilizing grasp. This prevents the object from escaping the hand, and allows for great position uncertainty of the fingers relative to the object. The hand is then closed until the desired immobilizing grasp is reached.

While efficient computation of two-finger caging grasps for polygonal objects is well developed, the computation of three-finger caging grasps has remained a challenging open problem. We will discuss the caging of polygonal objects using three-finger hands that maintain similar triangle finger formations during the grasping process. While the configuration space of such hands is four dimensional, their contact space which represents all two and three finger contacts along the grasped object's boundary forms a two-dimensional stratified manifold.

We will present a caging graph that can be constructed in the hand's relatively simple contact space. Starting from a desired immobilizing grasp of the object by a specific triangular finger formation, the caging graph is searched for the largest formation scale value that ensures a three-finger cage about the object. This value determines the caging regions, and if the formation scale is kept below this value, any finger placement within the caging regions will guarantee a robust object grasping.

ThursdayFeb 01, 201812:15
Vision and Robotics SeminarRoom 1
Speaker:Haggai MaromTitle:TBAAbstract:opens in new windowin html    pdfopens in new window