Modeling of micro-scale touch sensations for use with haptically augmented reality

Possessing dexterity and sensory perceptions, the human hand is a versatile tool that can grasp, hold, and manipulate objects using various postures and forces interacting with the environment. Many industrial tasks are replacing human hands with anthropomorphic robotic hands. In skillful tasks such as micro surgical operations, a master-slave interface system of robotic hands is required to emulate a human hand's dexterity by using glove controllers with force sensors for telemanipulation. Although these interface techniques are widely applied for large scale robots, little has been accomplished for micro-scale robots due to the constraints and complexity imposed by miniaturization. To provide sensible haptic control and feedback from robots at the micro-level, this work investigates the intricacies associated with the use of micro-scale robotic actuators with the intention of using them with haptic feedback systems. This work also develops a system model to test the ability of computing elements that emulate a microrobotic hand's tactile perception of stiffness. An interface glove was used to collect control data from the user, which was used alongside a Matlab model to simulate the operation and control of two different microhand designs. In order to control the microhand device accurately, feedback from simulated sensors was used to affect the airflow of the pneumatic system driving the displacement of the microhand. Four major components were developed for the overall system. The glove interface gives the operator a method to interact with the system. The microhand modeling took place in two components. The first component was the model of the microhand itself. The other component needed was a pneumatic subsystem to drive the microhand operation. The final major component developed was a graphical user interface to give the operator feedback as to what is happening in the target environment. The integration of all of these components allows for experimentation of the intricacies of operating with these microhand devices. The investigation of this micro-haptic system shows that some parameters make the system perform faster and more accurately than others. Metrics such as percent error and settling time of the displacement of one micro-finger are shown to measure success of each method. Future improvements for this system could include the integration of pneumatically controlled balloon micro-actuators with the operator's glove interface or implementing more accurate contact mechanics into the model.