B. Shih, D. Drotman, C. Christianson, Z. Huo, R. White, H. I.Christensen, and M. T. Tolley, "Custom soft
robotic gripper sensor skins for haptic object visualization," in 2017 IEEE/RSJ International Conference
on Intelligent Robots and Systems (IROS), pp. 494-501, Sept 2017.
Tactile sensing is an important capability for robots that assist or interact with humans or fragile objects in uncertain environments. An ongoing challenge for soft robots has been incorporating sensors that can recognize complex motions. We present sensor skins that enable haptic object visualization when integrated on a soft robotic gripper that can twist an object. First, we investigate how the design of the actuator modules impact bend angle and motion. Each soft finger is molded using a silicone elastomer, and consists of three pneumatic chambers which can be inflated independently to achieve a range of complex motions. Three fingers are combined to form a soft robotic gripper. Then, we manufacture and attach modular, flexible sensory skins on each finger to measure deformation and contact. These sensor measurements are used in conjunction with an analytical model to construct 2D and 3D tactile object models. Our results are a step towards soft robot grippers capable of a complex range of motions and proprioception, which will help future robots better understand the environments with which they interact, and have the potential to increase physical safety in human-robot interaction.