A novel approach to real-time tracking of three-finger planar grasp points for deforming objects is proposed. The search space of possible grasping configurations is reduced in two stages - firstly, by fixing one finger at the boundary point nearest to the object centroid and secondly, through a heuristic partitioning of the object boundary where the remaining two fingers are localized. The potential grasping configurations satisfying force closure conditions are evaluated through an objective function that maximizes the grasping span while minimizing the distance between the object centroid and the intersection of the contour normals at the finger contact points. A population based stochastic search strategy is adopted for computing the optimal grasping configurations and re-localizing them as the shape undergoes drastic translations, rotations, scaling and local deformations. Experimental results of grasp point tracking are presented for deforming planar shapes extracted from both real and synthetic image sequences. The current implementation of the proposed scheme operates at 10 Hz for grasp point tracking on shapes extracted through visual feedback
['Tripuresh Mishra', 'Prithwijit Guha', 'Ashish Dutta', 'K. S. Venkatesh']
Efficient continuous re-grasp planning for moving and deforming planar objects