Improving ASTRO's Perception Capability for a more Natural Follow-Me Task

Social assistive robots usually encompass a great compromise between the advanced perception models that one can use and their computing capabilities. The ideal approaches are always oriented towards low power consumption while maintaining a higher order of responsiveness to the surroundings. Therefore, we present in this paper, an improvement of the follow-me system on ASTRO. In detail, we propose the use of Mediapipe SDK for human detection and tracking, when ASTRO is meant to accompany someone that is walking. A study on the new velocity and distance profiles that the robot keeps from the individuals is presented and we have also evaluated how it affects their perception of being safe. The presented results show that our new approach allows the system to achieve real-time performance by becoming
$\approx 9.1\times \mathbf{faster}$
, smoothing, and keeping a more natural distance from the user.