Decomposition of Multimodal Data for Affordance-based Identification of Potential Graps

In this paper, we apply standard decomposition approaches to the problem of finding local correlations in multi-modal and high-dimensional grasping data, particularly to correlate the local shape of cup-like objects to their associated local grasp configurations. We compare the capability of several decomposition methods to establish these task-relevant, inter-modal correlations and indicate how they can be exploited to find potential contact points and hand postures for novel, though similar, objects.