Abstract Interaction in virtual reality (VR) environments (e.g. grasping and manipulating virtual objects) is essential to ensure a pleasant and immersive experience. In this work, we propose a visually realistic, flexible and robust grasping system that enables real-time interactions in virtual environments. Resulting grasps are visually realistic because hand is automatically fitted to the object shape from a position and orientation determined by the user using the VR handheld controllers (e.g. Oculus Touch motion controllers). Our approach is flexible because it can be adapted to different hand meshes (e.g. human or robotic hands) and it is also easily customizable. Moreover, it enables interaction with different objects regardless their geometries. In order to validate our proposal, an exhaustive qualitative and quantitative performance analysis has been carried out. On one hand, qualitative evaluation was used in the assessment of abstract aspects, such as motor control, finger movement realism, and interaction realism. On the other hand, for the quantitative evaluation a novel metric has been proposed to visually analyze the performed grips. Performance analysis results indicate that previous experience with our grasping system is not a prerequisite for an enjoyable, natural and intuitive VR interaction experience.
Grasping action is the most basic component of any interaction and it is composed of three major components @cite_21 . The first one is related to the process of approaching the arm and hand to the target object, considering the overall body movement. The second component focuses on the hand and body pre-shaping before the grasping action. Finally, the last component fits the hand to the geometry of the object by closing each of the fingers until contact is established.
@cite_21
1999329153
Animated human characters in everyday scenarios must interact with the environment using their hands. Captured human motion can provide a database of realistic examples. However, examples involving contact are difficult to edit and retarget; realism can suffer when a grasp does not appear secure or when an apparent impact does not disturb the hand or the object. Physically based simulations can preserve plausibility through simulating interaction forces. However, such physical models must be driven by a controller, and creating effective controllers for new motion tasks remains a challenge. In this paper, we present a controller for physically based grasping that draws from motion capture data. Our controller explicitly includes passive and active components to uphold compliant yet controllable motion, and it adds compensation for movement of the arm and for gravity to make the behavior of passive and active components less dependent on the dynamics of arm motion. Given a set of motion capture grasp examples, our system solves for all but a small set of parameters for this controller automatically. We demonstrate results for tasks including grasping and two-hand interaction and show that a controller derived from a single motion capture example can be used to form grasps of different object geometries.