Design and Development of ExoGlove for Obtaining Human Hand Data

Skill transfer from a human hand to a robot hand is extremely challenging. Currently, researchers typically use mapping of human hand postures onto the robot hand with the help of a data glove. This approach to skill transfer has yielded impressive results for grasping applications, but is difficult to implement for fine manipulation tasks. Humans use their sense of touch to handle various objects to perform fine manipulation tasks such as stitching, calligraphy, carving, and painting. Consequently, it is also important to measure the tactile data exerted by the human hand on the object while performing fine manipulation tasks. Previously we presented FingerTac - a wearable tactile sensor that can be worn interchangeably on human hands as well as on robot hands. FingerTac is capable of measuring 3-axis tactile data distributed at 20 sensing points around the user's fingertip. In this paper we present ExoGlove (see Fig. 1), which is a combination of a mechanical exoskeleton and FingerTac. The mechanical joints of the ExoGlove are embedded with magnetic encoders which allow precise monitoring of joint angles between the human hand finger segments. As the ExoGlove is integrated with the FingerTac it allows roboticists to not only map the posture of the human hand to the robot hand but to also map the tactile data from the human hand while performing fine manipulation tasks. The sensor is able to measure angles with a mean absolute error of 2.76 degrees.