We rarely experience difficulty picking up objects, yet of all potential contact points on the surface, only a small proportion yield effective grasps. Here, we present extensive behavioral data alongside a normative model that correctly predicts human precision grasping of unfamiliar 3D objects. We tracked participants' forefinger and thumb as they picked up objects of 10 wood and brass cubes configured to tease apart effects of shape, weight, orientation, and mass distribution. Grasps were highly systematic and consistent across repetitions and participants. We employed these data to construct a model which combines five cost functions related to force closure, torque, natural grasp axis, grasp aperture, and visibility. Even without free parameters, the model predicts individual grasps almost as well as different individuals predict one another's, but fitting weights reveals the relative importance of the different constraints. The model also accurately predicts human grasps on novel 3D-printed objects with more naturalistic geometries and is robust to perturbations in its key parameters. Together, the findings provide a unified account of how we successfully grasp objects of different 3D shape, orientation, mass, and mass distribution.

Grasping is one of the fundamental actions we perform to interact with objects in real environments, and in the real world we rarely experience difficulty picking up objects. Grasping plays a fundamental role for interactive virtual reality (VR) systems that are increasingly employed not only for recreational purposes, but also for training in industrial contexts, in medical tasks, and for rehabilitation protocols. To ensure the effectiveness of such VR applications, we must understand whether the same grasping behaviors and strategies employed in the real world are adopted when interacting with objects in VR. To this aim, we replicated in VR an experimental paradigm employed to investigate grasping behavior in the real world. We tracked participants' forefinger and thumb as they picked up, in a VR environment, unfamiliar objects presented at different orientations, and exhibiting the same physics behavior of their real counterparts. We compared grasping behavior within and across participants, in VR and in the corresponding real world situation. Our findings highlight the similarities and differences in grasping behavior in real and virtual environments.