Crowd of Oz: a crowd-powered social robotics system for stress management

Tahir Abbas (Corresponding author), Panos Markopoulos, Javed Khan, Emilia I. Barakova

Research output: Contribution to journalArticleAcademicpeer-review

18 Citations (Scopus)
91 Downloads (Pure)


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.
Original languageEnglish
Article number569
Number of pages29
Issue number2
Publication statusPublished - 20 Jan 2020


  • social robotics
  • coaching
  • social conversation
  • crowdsourcing
  • human computation
  • real-time crowd-powered systems
  • stress
  • Crowdsourcing
  • Social conversation
  • Coaching
  • Human computation
  • Social robotics
  • Stress
  • Real-time crowd-powered systems
  • Stress, Psychological/therapy
  • Humans
  • Man-Machine Systems
  • Psychotherapy/methods
  • Crowdsourcing/methods
  • Algorithms
  • Speech
  • Robotics/methods
  • Communication


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