Automating Robotic Furniture with A Collaborative Vision-based Sensing Scheme

Abstract

Automating teleoperated robots is an essential task for transforming human-robot interaction design into practical applications. In this paper, we present a Collaborative Vision-based Sensing Scheme (CVSS) for automating mobile robotic furniture in the household environment. Using multiple cameras to perceive users' spatial information and capture their body postures respectively, our sensing scheme can provide formerly teleoperated robots with sufficient situational awareness of the users' surroundings and enable them to understand the interactive willingness of humans. As an application instance, we introduce the design of a furniture-type robot, called Automan, whose prototype is a teleoperated mechanical ottoman reported in [1]. Utilizing CVSS, we enable Automan the similar functions as teleoperated ottoman to offer and withdraw services for humans. To evaluate our automation method, we conducted the subjective experiments with 20 participants to verify the effectiveness of it in comparison with the teleoperated ottomans in terms of interactive experience. And the result of paired samples t test indicates that the participants can't significantly distinguish whether the interactive ottoman is autonomous or teleoperated (p≫0.05). Furthermore, we also explored and analyzed users' satisfaction for different behavior styles between autonomous and teleoperated ottomans.