Abstract
The current technology has provided the necessary means for creating better assistive tools. Among these tools, the interest on assistive robotics has been growing, since its cost is being reduced and new equipment is introduced on the market. Yet, developing robots for aiding therapy is not an easy task because robotics is intrinsically multidisciplinary. Among the several research fields contributing to robotics research, two are of particular interest: control architectures and human–robot interaction. This paper covers ongoing research projects on assistive mobile robots for child rehabilitation developed in collaboration with Brazilian and Colombian Universities and proposes an intelligent control architecture based on human–robot interaction for assistive applications. Furthermore, it presents a case study on assistive robots for special education.
Similar content being viewed by others
References
Arkin, R. C. (1988). Behavior-based robotics. Cambridge: MIT Press.
Arkin, R. C. (1989). Motor schema—based mobile robot navigation. The International Journal of Robotics Research, 8(4), 92–112.
Atkinson, R. C., & Shiffrin, R. M. (1968). Human memory: A proposed system and its control processes. The Psychology of Learning and Motivation, 2, 89–195.
Burke, J., Murphy, R., Rogers, E., Lumelsky, V., & Scholtz, J. (2004). Final report for the DARPA/NSF interdisciplinary study on human-robot interaction. IEEE Transactions on Systems, Man and Cybernetics, Part C (Applications and Reviews), 34(2), 103–112.
Coeckelbergh, M., Pop, C., Simut, R., Peca, A., Pintea, S., David, D., et al. (2015). A survey of expectations about the role of robots in robot-assisted therapy for children with ASD: Ethical acceptability, trust, sociability, appearance, and attachment. Science and Engineering Ethics, 22(1), 47–65. doi:10.1007/s11948-015-9649-x.
Dautenhahn, K., & Billard, A. (2002). Games children with autism can play with robota, a humanoid robotic doll. In S. Keates, P. Langdon, P. J. Clarkson, & P. Robinson (Eds.), Universal Access and Assistive Technology: Proceedings of the Cambridge Workshop on UA and AT ’02 (pp. 179–190). London: Springer London. doi:10.1007/978-1-4471-3719-1_18.
Duquette, A., Michaud, F., & Mercier, H. (2007). Exploring the use of a mobile robot as an imitation agent with children with low-functioning autism. Autonomous Robots, 24(2), 147–157.
Du, G., & Zhang, P. (2015). A markerless human-robot interface using particle filter and kalman filter for dual robots. IEEE Transactions on Industrial Electronics, 62(4), 2257–2264.
Ekman, P. (1999). Handbook of cognition and emotion. In T. Dalgleish & M. J. Power (Eds.), Basic emotions (pp. 45–60). John Wiley & Sons, Ltd.
Emery, N. J. (2000). The eyes have it: The neuroethology, function and evolution of social gaze. Neuroscience and Biobehavioral Reviews, 24(6), 581–604.
Gazzaniga, M., Heatherton, T., & Halpern, D. (2012). Motivation and emotion. In Psychological science (4th ed.). New York, NY: W.W. Norton & Company.
Goodrich, M. A., Colton, M. A., Brinton, B., & Fujiki, M. (2011). A case for low-dose robotics in autism therapy. In Proceedings of the 6th international conference on Human-robot interaction (pp. 143–144).
Goodrich, M. A., & Schultz, A. C. (2007). Human-robot interaction: a survey. Foundations and Trends in Human-Computer Interaction, 1(3), 203–275.
Han, M. J., Lin, C. H., & Song, K. T. (2013). Robotic emotional expression generation based on mood transition and personality model. IEEE Transactions on Cybernetics, 43(4), 1290–1303.
Iacono, I., Lehmann, H., Marti, P., Robins, B., Dautenhahn, K. (2011). Robots as social mediators for children with Autism—A preliminary analysis comparing two different robotic platforms. In 2011 IEEE International Conference on Development and Learning (ICDL) (Vol. 2, pp. 1–6).
Jakoi, E., & Carbrey, J. (2015). Introductory Human Physiology. Lulu.com. http://www.lulu.com/shop/emma-jakoi-and-jennifer-carbrey/introductory-human-physiology/ebook/product-22080962.html.
Kim, E., Paul, R., Shic, F., & Scassellati, B. (2012). Bridging the research gap: Making HRI useful to individuals with autism. Journal of Human-Robot Interaction, 1, 26–54.
Larue, O., Poirier, P., & Nkambou, R. (2013). The emergence of (artificial) emotions from cognitive and neurological processes. Biologically Inspired Cognitive Architectures, 4, 54–68.
Maslow, A. H. (1943). A theory of human motivation. Psychological Review, 50(4), 370–396.
Mulligan, K., & Scherer, K. R. (2012). Toward a working definition of emotion. Emotion Review, 4(4), 345–357.
Pereira, F. G., Vassallo, R. F., & Salles, E. O. T. (2013). Human-robot interaction and cooperation through people detection and gesture recognition. Journal of Control, Automation and Electrical Systems, 24(3), 187–198.
Posner, J., Russell, J. A., & Peterson, B. S. (2005). The circumplex model of affect: An integrative approach to affective neuroscience, cognitive development, and psychopathology. Development and Psychopathology, 17(3), 715–734.
Reilent, E. (2012). Whiteboard architecture for the multi-agent sensor systems. Doctoral thesis, Tallinn University of Technology, Tallinn, Estônia.
Robins, B., Dautenhahn, K., Nehaniv, C. L., Mirza, N. A., François, D., & Olsson, L. (2005). Sustaining interaction dynamics and engagement in dyadic child-robot interaction kinesics: Lessons learnt from an exploratory study. In Robot and Human Interactive Communication, 2005. ROMAN 2005. IEEE International Workshop on (pp. 716–722).
Robins, B., Ferrari, E., Dautenhahn, K., Kronreif, G., Prazak-Aram, B., Gelderblom, G. J., et al. (2010). Human-centred design methods: Developing scenarios for robot assisted play informed by user panels and field trials. International Journal of Human-Computer Studies, 68(12), 873–898.
Russell, J. A. (1980). A circumplex model of affect. Journal of Personality and Social Psychology, 39(6), 1161–1178.
Sellers, M. (2013). Toward a comprehensive theory of emotion for biological and artificial agents. Biologically Inspired Cognitive Architectures, 4, 3–26.
Thórisson, K. R., List, T., Pennock, C., & DiPirro, J. (2005). Whiteboards: Scheduling blackboards for semantic routing of messages and streams. In AAAI-05 Workshop on Modular Construction of Human-Like Intelligence (pp. 8–15).
Valadão, C., Bastos, T., Bor̂tole, M., Perim, V., Celino, D., Rodor, F., et al. (2011). Educational robotics as a learning aid for disabled children. In Biosignals and Biorobotics Conference (BRC), 2011 ISSNIP (pp. 1–6).
Villa-Parra, A. C., Broche, L., Delisle-Rodríguez, D., Sagaró, R., Bastos, T., & Frizera-Neto, A. (2015). Design of active orthoses for a robotic gait rehabilitation system. Frontiers of Mechanical Engineering, 10(3), 242–254.
Viola, P., & Jones, M. (2001). Rapid object detection using a boosted cascade of simple features. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR (Vol. 1, pp. I-511–I-518).
Zhang, J., & Sharkey, A. J. C. (2012). It’s not all written on the robot’s face. Robotics and Autonomous Systems, 60(11), 1449–1456.
Acknowledgments
We thank the Group of Integration of Intelligent Systems and Devices (GISDI), of the Department of Computing, Faculty of Sciences, São Paulo State University, Bauru, Brazil. We also thank the Laboratory of Intelligent Automation (LAI), of the Department of Electrical Engineering, Center for Technology, Federal University of Espírito Santo, Vitória, Brazil, for their support. We also thank Freepik for the pictographs and to Kevin MacLeod for the music.
Author information
Authors and Affiliations
Corresponding author
Additional information
This work was supported by São Paulo Research Foundation under Grants 2011/17610-0 and 2012/12050-0.
Rights and permissions
About this article
Cite this article
dos Reis Alves, S.F., Ferasoli Filho, H. Intelligent Control Architecture for Assistive Mobile Robots. J Control Autom Electr Syst 27, 515–526 (2016). https://doi.org/10.1007/s40313-016-0249-z
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s40313-016-0249-z