A Modeling and Control Strategy for the Gaze-Guided Teleoperation of Robotic Manipulators via Smart Glasses

Abstract

Object manipulation is a high-frequency task required in assistive robotic systems in order to aid the elderly or those with disabilities that impact motor control. In the instance where arms cannot be used to command a robot, gaze-tracking via smart glasses is a suitable candidate. In this work, we develop a modeling method and model-based filtering and control strategy for direct gaze-guided teleoperation of robotic manipulators. We demonstrate the feasibility of this control strategy in an object manipulation case study with six participants. The results indicate that a model-based gaze filtering and control strategy produces smooth commands for the robot that are easy for the participants to use. These methods can reduce the perceived workload of the user by 37.51% and lower the gripper positioning error by 39.09% compared to using unfiltered gaze data.