Crowd of oz

A crowd-powered social robotics system for stress management

verfasst von

Tahir Abbas, Vassilis Javed Khan, Ujwal Gadiraju, Emilia Barakova, Panos Markopoulos

Abstract

Coping with stress is crucial for a healthy lifestyle. In the past, a great deal of research has been conducted to use socially assistive robots as a therapy to alleviate stress and anxiety related problems. However, building a fully autonomous social robot which can deliver psycho-therapeutic solutions is a very challenging endeavor due to limitations in artificial intelligence (AI). To overcome AI’s limitations, researchers have previously introduced crowdsourcing-based teleoperation methods, which summon the crowd’s input to control a robot’s functions. However, in the context of robotics, such methods have only been used to support the object manipulation, navigational, and training tasks. It is not yet known how to leverage real-time crowdsourcing (RTC) to process complex therapeutic conversational tasks for social robotics. To fill this gap, we developed Crowd of Oz (CoZ), an open-source system that allows Softbank’s Pepper robot to support such conversational tasks. To demonstrate the potential implications of this crowd-powered approach, we investigated how effectively, crowd workers recruited in real-time can teleoperate the robot’s speech, in situations when the robot needs to act as a life coach. We systematically varied the number of workers who simultaneously handle the speech of the robot (N = 1, 2, 4, 8) and investigated the concomitant effects for enabling RTC for social robotics. Additionally, we present Pavilion, a novel and open-source algorithm for managing the workers’ queue so that a required number of workers are engaged or waiting. Based on our findings, we discuss salient parameters that such crowd-powered systems must adhere to, so as to enhance their performance in response latency and dialogue quality.

Organisationseinheit(en)

Forschungszentrum L3S

Externe Organisation(en)

Eindhoven University of Technology (TU/e)
Mirpur University of Science and Technology (MUST)

Typ

Artikel

Journal

Sensors (Switzerland)

Band

20

ISSN

1424-8220

Publikationsdatum

20.01.2020

Publikationsstatus

Veröffentlicht

Peer-reviewed

Ja

ASJC Scopus Sachgebiete

Analytische Chemie, Biochemie, Atom- und Molekularphysik sowie Optik, Instrumentierung, Elektrotechnik und Elektronik

Ziele für nachhaltige Entwicklung

SDG 3 – Gute Gesundheit und Wohlergehen

Elektronische Version(en)

https://doi.org/10.3390/s20020569 (Zugang: Offen)