Global Optimization of Robotic Grasps

This paper presents a procedure to optimize the quality of robotic grasps for objects that need to be held and manipulated in a specific way, characterized by a number of tight contact constraints. The main difficulties of the problem include that the set of feasible grasps is a manifold implicitly defined by a system of non-linear equations, the high dimension of this manifold, and the multi-modal nature of typical grasp quality indices, which make local optimization methods get trapped into local extrema. The proposed procedure finds a way around these difficulties by focussing the exploration on a relevant subset of grasps of lower dimension, which is traced out exhaustively using higher-dimensional continuation techniques. Using these techniques, a detailed atlas of the subset is obtained, on which the highest quality grasp according to any desired criterion can be readily identified. Experiments on a 3-finger planar hand and on the Schunk anthropomorphic hand validate the approach.