Training Eye-Hand Coordination in Simulated Interception With Gaze-Informed Haptic Guidance

Despite the fact that robotic platforms can assist user in training tasks requiring eye-hand coordination (EHC) motor skills, there are few instances where the robot-assisted training paradigm is more effective than unassisted practice for skill acquisition. This may be largely due to the reason that current studies on robotic EHC training have elucidated several challenges, such as large-delay gaze-based feedforward predictions of participant's focused-object and unintuitive augmented feedback for delivering skill characteristics. To this end, we develop a novel robotic training paradigm with gaze-informed haptic guidance for enhancing EHC learning in a simulated spatiotemporally critical interception task. Its gaze interface accurately captures the participant's visual attention on virtual moving object with only ~200ms latency (much shorter than ~2s of current studies), and then the robot immediately activates the kinesthetic feedback for teaching fine motions (when and how to move) facilitating successful interceptions. In this way, the proposed paradigm exhibits features previously shown to promote successful training: It avoids disruptive delays between the user's attention before hand movement and the task-specific robotic assistance, assisting trainees in completing the interception more frequently when it is in use; It encourages user engagement, since the participant's intentional focus has to be detected explicitly during training; It provides meaningful haptic guidance to the less-skilled learner for spatiotemporally critical tasks. Through user studies, we showed that the proposed robotic training paradigm with attention-triggered task-specific haptic feedback led to increased skill acquisition compared with unassisted practice.