Design and Evaluation of a Unique Social Perception System for Human–Robot Interaction

Abstract

Robot's perception is essential for performing highlevel tasks such as understanding, learning, and in general, human-robot interaction (HRI). For this reason, different perception systems have been proposed for different robotic platforms in order to detect high-level features such as facial expressions and body gestures. However, due to the variety of robotics software architectures and hardware platforms, these highly customized solutions are hardly interchangeable and adaptable to different HRI contexts. In addition, most of the developed systems have one issue in common: they detect features without awareness of the real-world contexts (e.g., detection of environmental sound assuming that it belongs to a person who is speaking, or treating a face printed on a sheet of paper as belonging to a real subject). This paper presents a novel social perception system (SPS) that has been designed to address the previous issues. SPS is an outof-the-box system that can be integrated into different robotic platforms irrespective of hardware and software specifications. SPS detects, tracks and delivers in real-time to robots, a wide range of human-and environment-relevant features with the awareness of their real-world contexts. We tested SPS in a typical scenario of HRI for the following purposes: to demonstrate the system capability in detecting several high-level perceptual features as well as to test the system capability to be integrated into different robotics platforms. Results show the promising capability of the system in perceiving real world in different social robotics platforms, as tested in two humanoid robots i.e., FACE and ZENO.

Computer Simulation of Human-Robot Collaboration in the Context of Industry Revolution 4.0

“…Hence, the robot's perception is a key issue for performing high-level tasks such as understanding and learning human-robot interaction. This perception can be detected from the high-level features of human facial expression and body gestures [71]. The perception systems are proposed in [71], but the variety of robotic software architecture and hardware platforms would make the customized solutions hardly interchangeable and adaptable for different human-robot interaction contexts.…”

“…This perception can be detected from the high-level features of human facial expression and body gestures [71]. The perception systems are proposed in [71], but the variety of robotic software architecture and hardware platforms would make the customized solutions hardly interchangeable and adaptable for different human-robot interaction contexts. Another aspect of learning (in control point of view) for the humanoid robot is, for example, in the situation when the robot is falling to the ground.…”

Designing the Mind of a Social Robot

“…In particular, the FACE robot is equipped with a social scene analysis system [30,31] aimed at acquiring "the robot Umwelt" by extracting social information related to the current context [R. 7]. The perception system of the FACE control architecture creates contextualized representations of the the FACE robot's Umwelt called social meta scenes (SMSs).…”

“…Finally, the meta-scene is serialized and sent over the network through its corresponding YARP port. Details of the scene analyzer algorithms and processes are reported in [30,39].…”

A Multimodal Perception Framework for Users Emotional State Assessment in Social Robotics

“…A detailed description of the Scene Analyzer is available in our previous works [39,41], where it is also provided the validation of the software and a useful instrument for the arrangement of HRI experiments with SA. Moreover, SA is delivered as an open-source software available on Github (https://github.com/FACE-Team/SceneAnalyzer-2.0).…”