Voice for ROS


Natural language is an important part of communication since it offers an intuitive and efficient way of conveying ideas to another individual. Enabling robots to efficiently use language is essential for human-robot collaboration. In this project, we aim to develop an interface between a dialog manager (i.e. DialogFlow) and ROS (Robotics Operating System). By doing this, we will be able to use the powerful dialogue systems in human-robot interaction scenario.


A scenario, using tangible robots (Cellulo) combined with voice assistant for upper-arm rehabilitation will be implemented to show the potential of this new ros-package.

Goals & Milestones

During this project, the student will:

  • Learn about Google DialogFlow and ROS
  • Develop a ROS package that enables to access and manipulates DialogFlow features
  • Develop a Cellulo Rehabilitation Game
  • Test the game with a pilot experiment


Voice-Assistant, Human-Robot Interaction, ROS


  • Skills: Python, C++, ROS, Git.


  • https://dialogflow.com/
  • https://www.ros.org/
  • http://wafa.johal.org/project/cellulo/
  • Hudson, C., Bethel, C. L., Carruth, D. W., Pleva, M., Juhar, J., & Ondas, S. (2017, October). A training tool for speech driven human-robot interaction applications. In 2017 15th International Conference on Emerging eLearning Technologies and Applications (ICETA) (pp. 1-6). IEEE.
  • Moore, R. K. (2017). Is spoken language all-or-nothing? Implications for future speech-based human-machine interaction. In Dialogues with Social Robots (pp. 281-291). Springer, Singapore.
  • Beirl, D., Yuill, N., & Rogers, Y. (2019). Using Voice Assistant Skills in Family Life. In Lund, K., Niccolai, G. P., Lavoué, E., Gweon, C. H., & Baker, M. (Eds.), A Wide Lens: Combining Embodied, Enactive, Extended, and Embedded Learning in Collaborative Settings, 13th International Conference on Computer Supported Collaborative Learning (CSCL) 2019, Volume 1 (pp. 96-103). Lyon, France: International Society of the Learning Sciences.