Preliminary Testing Of A Telerobotic Haptic System And Analysis Of Visual Attention During A Playful Activity
Children with physical impairments face great challenges to play because of their limitations, for example, in reaching and grasping objects. Studies have shown that children with physical impairments can improve their independence, cognitive, and social skills by playing using robots. Haptic robots can provide the sense of touch, and implement haptic guidance to help users reach objects. In this study, we developed a telerobotic haptic system with two haptic robots. The goal of this study was to do preliminary tests of the haptic guidance method and the prediction of targets. Another goal was to analyze the visual attention of the participants during the activity when eye-hand discoordination was induced. Five adults without disabilities played a whack-a-mole game using the robotic system, to assure that the robot works adequately before children with disabilities use it. The robots were programmed to induce eye-hand discoordination, so that haptic guidance would be required. A multi-layer perceptron neural network was implemented to predict the target moles that the participants had to reach, which in future versions, will allow generation of forbidden region virtual fixtures (FRVF) to guide the user towards the target moles. Analysis of participant's eye gaze led to the hypothesis that the less control a person has over the teleoperation system, the less they will look at the target. On average, the accuracy of the target prediction by the neural network was 70.7%. The predicting of targets will allow the robot to assist children during movement of the robot towards the target toy, without needing the children to explicitly point out with their gaze which toy they want to reach. This will potentially lead to a more intuitive and faster human-robot interaction.