CLAW extends the concept of a VR controller to a multifunctional haptic tool, using a single motor. At first glance, it looks very similar to your standard VR controller. A closer look reveals a unique motorized arm that rotates the index finger relative to the palm to simulate force feedback.
CLAW acts as a multi-purpose controller that contains both the expected functionality of VR controllers (thumb buttons and joysticks, 6DOF control, index finger trigger) as well as enabling a variety of haptic renderings for the most commonly expected hand interactions: grasping objects, touching virtual surfaces and receiving force feedback. But a unique characteristic of the CLAW is its ability to adapt haptic rendering by sensing differences in the user’s grasp and the situational context of the virtual scene. As a user holds a thumb against the tip of the finger, the device simulates a grasping operation: the closing of the fingers around a virtual object is met with a resistive force, generating a sense that the object lies between the index finger and the thumb. A force sensor embedded in the index finger rest and changing the motor’s response profiles enables the sensing of objects of different materials, from full rigid wooden block to an elastic sponge. If the user holds the thumb away from a grasp pose, for example on the handle, shaping the palm instead in a pointing gesture, the controller delivers touch sensations. Moving the tip of the finger toward a surface of a virtual objects generates a resistance that pushes the finger back and prevents the finger from penetrating the virtual surface. Furthermore, a voice coil mounted under the tip of the index finger delivers small vibrations generated by surface texture as the finger slides along a virtual surface. Sensing the force applied by the user can also help to interact with virtual objects. Pushing a slider allows the experienced friction to signal preferable states or pressure can change attributes of a paint brush or pen in a drawing program.
CLAW was realized with the aid of Inrak Choy, an intern from Stanford University.