Predicting precision grip grasp locations on three-dimensional objects
Fig 6
A framework that unifies distinct aspects of grasp selection.
(a) Mesh model of object in same 3D reference frame as participant poised to execute grasp. (b) Discrete sampling of the reachable surface defines a 2D space containing all potential combinations of index and thumb contact points on the object. (c) Color-coded maps showing penalty values for each potential grasp for each penalty function. (d) Overall penalty function computed as the linear combination of maps in (c). (e) Human grasps projected into 2D penalty-function space neatly align with minimum of combined penalty map.