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Introduction to Human Robot Interaction

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Smart Maintenance for Human–Robot Interaction

Part of the book series: Studies in Systems, Decision and Control ((SSDC,volume 129))

Abstract

This chapter introduces some general knowledge relative to the broad area of human robot interaction (HRI). The exceptional achievements made by a variety of novel robots have motivated scholars to continually develop the next generation of robots in terms of their safety and dependability. Some background information of HRI are presented in Sect. 1.1 from physical and cognitive perspectives, respectively. Then, an extended HRI classification (used throughout this book) is briefed in Sect. 1.2. Section 1.3 summarises this chapter.

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References

  • Anandan, T. M. (2017). Robots, humans collaborate on safety. Control Engineering, 24–27 (May).

    Google Scholar 

  • Araujo, A. R., Caminhas, D. D., & Pereira, G. A. S. (2015). An architecture for navigation of service robots in human-populated office-like environments. IFAC-PapersOnLine, 48–19, 189–194.

    Article  Google Scholar 

  • Argall, B. D., & Billard, A. G. (2010). A survey of tactile human–robot interactions. Robotics and Autonomous Systems, 58, 1159–1176.

    Article  Google Scholar 

  • Argall, B. D., Chernova, S., Veloso, M., & Browning, B. (2009). A survey of robot learning from demonstration. Robotics and Autonomous Systems, 57, 469–483.

    Article  Google Scholar 

  • Ayers, J., Davis, J. L., & Rudolph, A. (Eds.). (2002). Neurotechnology for biomimetic robots. London, England: The MIT Press. ISBN 0-262-01193-X.

    Google Scholar 

  • Bajd, T., Mihelj, M., Lenarčič, J., Stanovnik, A., & Munih, M. (2010). Robotics. Dordrecht, Heidelberg, London, New York: Springer Science + Business Media B.V. ISBN 978-90-481-3775-6.

    Google Scholar 

  • Balaguer, C., & Abderrahim, M. (Eds.). (2008). Robotics and automation in construction. Vienna, Austria: In-teh. ISBN 978-953-7619-13-8.

    Google Scholar 

  • Bdiwi, M. (2014). Integrated sensors system for human safety during cooperating with industrial robots for handing-over and assembling tasks. Procedia CIRP, 23, 65–70.

    Article  Google Scholar 

  • Bdiwi, M., Pfeifer, M., & Sterzing, A. (in press). A new strategy for ensuring human safety during various levels of interaction with industrial robots. CIRP Annals—Manufacturing Technology. http://dx.doi.org/10.1016/j.cirp.2017.04.009.

  • Bechar, A., & Vigneault, C. (2017). Agricultural robots for field operations. Part 2: Operations and systems. Biosystems Engineering, 153, 110–128.

    Article  Google Scholar 

  • Bergerman, M., Billingsley, J., Reid, J., & van Henten, E. (2016). Robotics in agriculture and forestry. In B. Siciliano & O. Khatib (Eds.), Handbook of robotics (2nd ed., pp. 1463–1492). Berlin, Heidelberg: Springer. ISBN 978-3-319-32550-7 (Part F, Chapter 56).

    Google Scholar 

  • Bertelsen, A., Melo, J., Sánchez, E., & Borro, D. (2013). A review of surgical robots for spinal interventions. International Journal of Medical Robotics and Computer Assisted Surgery, 9, 407–422.

    Article  Google Scholar 

  • Bicchi, A., & Tonietti, G. (2004). Fast and soft arm tactics: dealing with the safety-performance trade-off in robot arms design and control. IEEE Robotics and Automation Magazine, 11, 22–33.

    Article  Google Scholar 

  • Bien, Z., & Chung, M.-J. (2004). Integration of a rehabilitation robotic system (KARES II) with human-friendly man-machine interaction units. Autonomous Robots, 16, 165–191.

    Article  Google Scholar 

  • Billard, A. G., Calinon, S., & Dillmann, R. (2016). Learning from humans. In B. Siciliano & O. Khatib (Eds.), Handbook of robotics (2nd ed., pp. 1995–2014). Berlin, Heidelberg: Springer. ISBN 978-3-319-32550-7 (Part G, Chapter 74).

    Google Scholar 

  • Bock, T., & Linner, T. (2016). Construction robot: Elementary technologies and single-task construction robots. USA: Cambridge University Press. ISBN 978-1-107-07599-3.

    Google Scholar 

  • Breazeal, C., Dautenhahn, K., & Kanda, T. (2016). Social robotics. In B. Siciliano & O. Khatib (Eds.), Handbook of robotics (2nd ed., pp. 1935–1971). Berlin, Heidelberg: Springer. ISBN 978-3-319-32550-7 (Part G, Chapter 72).

    Google Scholar 

  • Broekens, J., Heerink, M., & Rosendal, H. (2009). Assistive social robots in elderly care: A review. Gerontechnology, 8(2), 94–103.

    Article  Google Scholar 

  • Broggi, A., Zelinsky, A., Özgüner, Ü., & Laugier, C. (2016). Intelligent vehicles. In B. Siciliano & O. Khatib (Eds.), Handbook of robotics (2nd ed., pp. 1627–1655). Berlin, Heidelberg: Springer. ISBN 978-3-319-32550-7 (Part F, Chapter 62).

    Google Scholar 

  • Bülthoff, H., Wallraven, C., & Giese, M. A. (2016). Perceptual robotics. In B. Siciliano & O. Khatib (Eds.), Handbook of robotics (2nd ed., pp. 2095–2113). Berlin, Heidelberg: Springer. ISBN 978-3-319-32550-7 (Part G, Chapter 78).

    Google Scholar 

  • Calo, R., Froomkin, A. M., & Kerr, I. (2016). Robot law. UK: Edward Elgar Publishing Limited. ISBN 978 1 78347 673 2.

    Google Scholar 

  • Canal, G., Escalera, S., & Angulo, C. (2016). A real-time human-robot interaction system based on gestures for assistive scenarios. Computer Vision and Image Understanding, 149, 65–77.

    Article  Google Scholar 

  • Catani, F., & Zaffagnini, S. (2013). Knee surgery using computer assisted surgery and robotics. Berlin: Springer. ISBN 978-3-642-31429-2.

    Google Scholar 

  • Chan, W. P., Parker, C. A. C., Van der Loos, H. F. M., & Croft, E. A. (2013). A human-inspired object handover controller. International Journal of Robotics Research, 32(8), 972–984.

    Google Scholar 

  • Chan, Z. (2015, July). Robots are coming: Living with robots and the dilemma of realizing true AI. HWM Singapore, pp. 29–31.

    Google Scholar 

  • Chao, F., Huang, Y., Zhang, X., Shang, C., Yang, L., Zhou, C., et al. (2017). A robot calligraphy system: From simple to complex writing by human gestures. Engineering Applications of Artificial Intelligence, 59, 1–14.

    Article  Google Scholar 

  • Cheng, G. (2015). Humanoid robotics and neuroscience: Science, engineering and society. USA: CRC Press, Taylor & Francis Group, LLC. ISBN 978-1-4200-9367-4.

    Google Scholar 

  • Cherubini, A., Passama, R., Crosnier, A., Lasnier, A., & Fraisse, P. (2016). Collaborative manufacturing with physical human–robot interaction. Robotics and Computer-Integrated Manufacturing, 40, 1–13.

    Article  Google Scholar 

  • Chibani, A., Amirat, Y., Mohammed, S., Matson, E., Hagita, N., & Barreto, M. (2013). Ubiquitous robotics: Recent challenges and future trends. Robotics and Autonomous Systems, 61, 1162–1172.

    Article  Google Scholar 

  • Choi, B. (Ed.). (2009). Humanoid robots. Austria: In-Tech. ISBN 978-953-7619-44-2.

    Google Scholar 

  • Christensen, H. I., & Hager, G. D. (2016). Sensing and estimation. In B. Siciliano & O. Khatib (Eds.), Handbook of robotics (2nd ed., pp. 91–112). Berlin, Heidelberg: Springer. ISBN 978-3-319-32550-7 (Part A, Chapter 5).

    Google Scholar 

  • Chun, W. H., & Papanikolopoulos, N. (2016). Robot surveillance and security. In B. Siciliano & O. Khatib (Eds.), Handbook of robotics (2nd ed., pp. 1605–1625). Berlin, Heidelberg: Springer. ISBN 978-3-319-32550-7 (Part F, Chapter 61).

    Google Scholar 

  • Cifuentes, C. A., Frizera, A., Carelli, R., & Bastos, T. (2014). Human–robot interaction based on wearable IMU sensor and laser range finder. Robotics and Autonomous Systems, 62, 1425–1439.

    Article  Google Scholar 

  • Coupeté, E., Moutarde, F., & Manitsaris, S. (2015). Gesture recognition using a depth camera for human robot collaboration on assembly line. Procedia Manufacturing, 3, 518–525.

    Article  Google Scholar 

  • Crespi, A., Badertscher, A., Guignard, A., & Ijspeert, A. J. (2005). AmphiBot I: An amphibious snake-like robot. Robotics and Autonomous Systems, 50, 163–175.

    Article  Google Scholar 

  • Dario, P., Guglielmelli, E., & Laschi, C. (2001). Humanoids and personal robots: Design and experiments. Journal of Robotic Systems, 18(12), 673–690.

    Article  MATH  Google Scholar 

  • Dorigo, M., Floreano, D., Gambardella, L. M., Mondada, F., Nolfi, S., Baaboura, T., … Vaussard, F. (2013). Swarmanoid: A novel concept for the study of heterogeneous robotic swarms. IEEE Robotics & Automation, 20(4), 60–71.

    Google Scholar 

  • Economist, T. (2013, September 7). Our friends electric. The Economist, Technology Quarterly, Vol. 408, Issue 8852, pp. 20–24.

    Google Scholar 

  • Engelberger, J. F. (1989). Robotics in service. Cambridge, Massachusetts: MIT Press. ISBN 0-262-05042-0.

    Google Scholar 

  • Erden, M. S., & Tomiyama, T. (2010). Human-intent detection and physically interactive control of a robot without force sensors. IEEE Transactions on Robotics, 26(2), 370–382.

    Article  Google Scholar 

  • Erol, D., & Sarkar, N. (2007). Design and implementation of an assistive controller for rehabilitation robotic systems. International Journal of Advanced Robotic Systems, 4(3), 271–278.

    Article  Google Scholar 

  • Ferreira, M. I. A., Sequeira, J. S., Tokhi, M. O., Kadar, E. E., & Virk, G. S. (2017). A world with robots. Switzerland: Springer International Publishing AG. ISBN 978-3-319-46665-1.

    Google Scholar 

  • Fitzpatrick, P., Harada, K., Kemp, C. C., Matsumoto, Y., Yokoi, K., & Yoshida, E. (2016). Humanoids. In B. Siciliano & O. Khatib (Eds.), Handbook of robotics (2nd ed., pp. 1789–1818). Berlin, Heidelberg: Springer. ISBN 978-3-319-32550-7 (Part G, Chapter 67).

    Google Scholar 

  • Fong, T., Kunz, C., Hiatt, L. M., & Bugajska, M. (2006). The human-robot interaction operating system. Paper presented at the Proceedings of the 1st ACM SIGCHI/SIGART Conference on Human-Robot Interaction, March 02–03, 2006, Salt Lake City, UT, USA, pp. 41–48.

    Google Scholar 

  • Genta, G. (2012). Introduction to the mechanics of space robots. Dordrecht, Heidelberg, London, New York: Springer Science + Business Media B.V. ISBN 978-94-007-1795-4.

    Google Scholar 

  • Giuliani, M., Lenz, C., Müller, T., Rickert, M., & Knoll, A. (2010). Design principles for safety in human-robot interaction. International Journal of Social Robotics, 2, 253–274.

    Article  Google Scholar 

  • Goldfield, E. C., Park, Y.-L., Chen, B.-R., Hsu, W.-H., Young, D., Wehner, M., et al. (2012). Bio-inspired design of soft robotic assistive devices: The interface of physics, biology, and behavior. Ecological Psychology, 24, 300–327.

    Article  Google Scholar 

  • González, J. C., Pulido, J. C., & Fernández, F. (2017). A three-layer planning architecture for the autonomous control of rehabilitation therapies based on social robots. Cognitive Systems Research, 43, 232–249.

    Article  Google Scholar 

  • Gopura, R. A. R. C., Bandara, D. S. V., Kiguchi, K., & Mann, G. K. I. (2016). Developments in hardware systems of active upper-limb exoskeleton robots: A review. Robotics and Autonomous Systems, 75, 203–220.

    Article  Google Scholar 

  • Guiochet, J., Machin, M., & Waeselynck, H. (2017). Safety-critical advanced robots: A survey. Robotics and Autonomous Systems, 94, 43–52.

    Article  Google Scholar 

  • Gunkel, D. J. (2012). The machine question: Critical perspectives on AI, robots, and ethics. Cambridge: MIT Press. ISBN 978-0-262-01743-5.

    Google Scholar 

  • Haddadin, S., Albu-Schäffer, A., Haddadin, F., Roßmann, J., & Hirzinger, G. (2011). Study on soft-tissue injury in robotics. IEEE Robotics and Automation Magazine, 18(4), 20–34.

    Article  Google Scholar 

  • Haddadin, S., & Croft, E. (2016). Physical human-robot interaction. In B. Siciliano & O. Khatib (Eds.), Handbook of robotics (2nd ed., pp. 1835–1874). Berlin, Heidelberg: Springer. ISBN 978-3-319-32550-7. (Part G, Chapter 69).

    Google Scholar 

  • Haddadin, S., Khoury, A., Rokahr, T., Parusel, S., Burgkart, R., Bicchi, A., et al. (2012). On making robots understand safety: Embedding injury knowledge into control. International Journal of Robotics Research, 31, 1578–1602.

    Article  Google Scholar 

  • Hägele, M., Nilsson, K., Pires, J. N., & Bischoff, R. (2016). Industrial robotics. In B. Siciliano & O. Khatib (Eds.), Handbook of robotics (2nd ed., pp. 1385–1421). Berlin, Heidelberg: Springer. ISBN 978-3-319-32550-7 (Part F, Chapter 54).

    Google Scholar 

  • Hamaya, M., Matsubara, T., Noda, T., Teramae, T., & Morimoto, J. (in press). Learning assistive strategies for exoskeleton robots from user-robot physical interaction. Pattern Recognition Letters. http://dx.doi.org/10.1016/j.patrec.2017.04.007.

  • Hirai, K. (1999). The Honda humanoid robot: Development and future perspective. Industrial Robot, 26(4), 260–266.

    Article  Google Scholar 

  • Hoenen, M., Lübke, K. T., & Pause, B. M. (2016). Non-anthropomorphic robots as social entities on a neurophysiological level. Computers in Human Behavior, 57, 182–186.

    Article  Google Scholar 

  • Hogan, N., & Buerger, S. P. (2005). Impedance and interaction control. In T. R. Kurfess (Ed.), Robotics and automation handbook (pp. 376–399). USA: CRC Press LLC. ISBN 0-8493-1804-1 (Chapter 19).

    Google Scholar 

  • Huang, C. M., & Mutlu, B. (2012). Robot behavior toolkit: Generating effective social behaviors for robots. Paper presented at the Proceedings of the 7th ACM/IEEE International Conference on Human-Robot Interaction, Boston, USA, pp. 25–32.

    Google Scholar 

  • Huang, X., Jia, Y., & Xu, S. (2017). Path planning of a free-floating space robot based on the degree of controllability. Science China Technological Sciences, 60(2), 251–263.

    Article  Google Scholar 

  • Huber, A., Lammer, L., Weiss, A., & Vincze, M. (2014). Designing adaptive roles for socially assistive robots: a new method ro reduce technological determinism and role stereotypes. Journal of Human-Robot Interaction, 3(2), 100–115.

    Article  Google Scholar 

  • Huber, S. A., Franz, M. O., & Bülthoff, H. H. (1999). On robots and flies: Modeling the visual orientation behavior of flies. Robotics and Autonomous Systems, 29, 227–242.

    Article  Google Scholar 

  • Hutchins, E. (1991). The social organization of distributed cognition. In L. B. Resnick, J. M. Levine, & S. D. Teasley (Eds.), Perspectives on socially shared cognition. Washington DC., USA: American Psychological Association. ISBN 9781557983763.

    Google Scholar 

  • Iida, F., & Ijspeert, A. J. (2016). Biologically inspired robotics. In B. Siciliano & O. Khatib (Eds.), Handbook of robotics (2nd ed., pp. 2015–2033). Berlin, Heidelberg: Springer. ISBN 978-3-319-32550-7 (Part G, Chapter 75).

    Google Scholar 

  • Ikemoto, S., Amor, H. B., Minato, T., Ishiguro, H., & Jung, B. (2012). Mutual learning and adaptation in physical human-robot interaction. Paper presented at the Proceedings of IEEE International Conference on Robotics and Automation (ICRA), May 14–18, 2012, USA, pp. 324–335.

    Google Scholar 

  • Indri, M., Trapani, S., & Lazzero, I. (2017). Development of a virtual collision sensor for industrial robots. Sensors, 17, 1148–1171.

    Article  Google Scholar 

  • ISO. (2014). ISO 13482: 2014: Robots and robotic devices—Safety requirements for personal care robots. Geneva, Switzerland: International Organization for Standardization (ISO).

    Google Scholar 

  • Jiménez-Fabián, R., & Verlinden, O. (2012). Review of control algorithms for robotic ankle systems in lower-limb orthoses, prostheses, and exoskeletons. Medical Engineering & Physics, 34, 397–408.

    Article  Google Scholar 

  • Jin, Z. (2015). Exploring implicit cognition: Learning, memory, and social cognitive processes. USA: IGI Global. ISBN 978-1-4666-6599-6.

    Google Scholar 

  • Joskowicz, L., Shoham, M., Shamir, R., Freiman, M., Zehavi, E., & Shoshan, Y. (2005). Miniature robot-based precise targeting system for keyhole neurosurgery: Concept and preliminary results. International Congress Series, 1281, 618–623.

    Article  Google Scholar 

  • Jung, S., & Hsia, T. C. (1998). Neural network impedance force control of robot manipulator. IEEE Transactions on Industrial Electronics, 45(3), 451–461.

    Article  Google Scholar 

  • Kamaleswari, P., Kumari, G. S., Rajasekar, R., & Kumar, A. J. G. (2013). Robotics for a heart operation and new trends in cardiorobotics (snake robot). International Journal of Advanced Research in Computer and Communication Engineering, 2(4), 1672–1676.

    Google Scholar 

  • Kaneko, S.-I., & Capi, G. (2014). Human-robot communication for surveillance of elderly people in remote distance. IERI Procedia, 10, 92–97.

    Article  Google Scholar 

  • Kaplan, F. (2004). Who is afraid of the humanoid? Investigating cultural differences in the acceptance of robots. International Journal of Humanoid Robot, 1(3), 465–480.

    Article  Google Scholar 

  • Kim, K. J., Park, E., & Sundar, S. S. (2013). Caregiving role in human–robot interaction: A study of the mediating effects of perceived benefit and social presence. Computers in Human Behavior, 29, 1799–1806.

    Article  Google Scholar 

  • Kruse, T., Pandey, A. K., Alami, R., & Kirsch, A. (2013). Human-aware robot navigation: A survey. Robotics and Autonomous Systems, 61, 1726–1743.

    Article  Google Scholar 

  • Lauretti, C., Cordella, F., Guglielmelli, E., & Zollo, L. (2017). Learning by demonstration for planning activities of daily living in rehabilitation and assistive Robotics. IEEE Robotics and Automation Letters, 2(3), 1375–1382.

    Article  Google Scholar 

  • Lee, S. (2011). Glazed panel construction with human-robot cooperation. New York, Dordrecht, Heidelberg, London: Springer. ISBN 978-1-4614-1417-9.

    Google Scholar 

  • Lenzi, T., Vitiello, N., Rossi, S. M. M. D., Persichetti, A., Giovacchini, F., Roccella, S., et al. (2011). Measuring human–robot interaction on wearable robots: A distributed approach. Mechatronics, 21, 1123–1131.

    Article  Google Scholar 

  • Leont’ev, A. N. (1974). The problem of activity in psychology. Journal of Russian and East European Psychology, 13(2), 4–33.

    Article  Google Scholar 

  • Liljebäck, P., Pettersen, K. Y., Stavdahl, Ø., & Gravdahl, J. T. (2012). A review on modelling, implementation, and control of snake robots. Robotics and Autonomous Systems, 60, 29–40.

    Article  MATH  Google Scholar 

  • Lima, D. A., & Oliveira, G. M. B. (in press). A cellular automata ant memory model of foraging in a swarm of robots. Applied Mathematical Modelling. doi:10.1016/j.apm.2017.03.021.

  • Liu, H., & Wang, L. (in press-a). Gesture recognition for human-robot collaboration: A review. International Journal of Industrial Ergonomics.

    Google Scholar 

  • Liu, H., & Wang, L. (in press-b). Human motion prediction for human-robot collaboration. Journal of Manufacturing Systems. http://dx.doi.org/10.1016/j.jmsy.2017.04.009.

  • Ma, Y., Xie, S., & Zhang, Y. (2016). A patient-specific EMG-driven neuromuscular model for the potential use of human-inspired gait rehabilitation robots. Computers in Biology and Medicine, 70, 88–98.

    Article  Google Scholar 

  • Makris, S., Karagiannis, P., Koukas, S., & Matthaiakis, A.-S. (2016). Augmented reality system for operator support in human–robot collaborative assembly. CIRP Annals—Manufacturing Technology, 65, 61–64.

    Article  Google Scholar 

  • Malik, N. A., Yussof, H., Hanapiah, F. A., Adawiah, R., Rahman, A., & Basri, H. H. (2015). Human-robot interaction for children with cerebral palsy: Reflection and suggestion for interactive scenario design. Procedia Computer Science, 76, 388–393.

    Article  Google Scholar 

  • Marshall, J. A., Bonchis, A., Nebot, E., & Scheding, S. (2016). Robotics in mining. In B. Siciliano & O. Khatib (Eds.), Handbook of robotics (2nd ed., pp. 1549–1576). Berlin, Heidelberg: Springer. ISBN 978-3-319-32550-7 (Part F, Chapter 59).

    Google Scholar 

  • Martini, S., Baccio, D. D., Romero, F. A., Jiménez, A. V., Pallottino, L., Dini, G., et al. (2015). Distributed motion misbehavior detection in teams of heterogeneous aerial robots. Robotics and Autonomous Systems, 74, 30–39.

    Article  Google Scholar 

  • Mastrogiovanni, F., & Sgorbissa, A. (2013). A behaviour sequencing and composition architecture based on ontologies for entertainment humanoid robots. Robotics and Autonomous Systems, 61, 170–183.

    Article  Google Scholar 

  • Matarić, M. J., & Scassellati, B. (2016). Socially assistive robotics. In B. Siciliano & O. Khatib (Eds.), Handbook of robotics (2nd ed., pp. 1973–1993). Berlin, Heidelberg: Springer. ISBN 978-3-319-32550-7 (Part G, Chapter 73).

    Google Scholar 

  • Mazzei, D., Maria, C. D., & Vozzi, G. (2016). Touch sensor for social robots and interactive objects affective interaction. Sensors and Actuators, A: Physical, 251, 92–99.

    Article  Google Scholar 

  • Michalos, G., Karagiannis, P., Makris, S., Tokçalar, Ö., & Chryssolouris, G. (2016). Augmented reality (AR) applications for supporting human-robot interactive cooperation. Procedia CIRP, 41, 370–375.

    Article  Google Scholar 

  • Miller, D. P., & Nourbakhsh, I. (2016). Robotics for education. In B. Siciliano & O. Khatib (Eds.), Handbook of robotics (2nd ed., pp. 2115–2134). Berlin, Heidelberg: Springer. ISBN 978-3-319-32550-7 (Part G, Chapter 79).

    Google Scholar 

  • Miller, R. M. (2008). Don’t let your robots grow up to be traders: Artificial intelligence, human intelligence, and asset-market bubbles. Journal of Economic Behavior & Organization, 68, 153–166.

    Article  Google Scholar 

  • Moustris, G. P., Hiridis, S. C., Deliparaschos, K. M., & Konstantinidis, K. M. (2011). Evolution of autonomous and semi-autonomous robotic surgical systems: A review of the literature. International Journal of Medical Robotics and Computer Assisted Surgery, 7, 375–392.

    Article  Google Scholar 

  • Murphy, R. R., Tadokoro, S., & Kleiner, A. (2016). Disaster robotics. In B. Siciliano & O. Khatib (Eds.), Handbook of robotics (2nd ed., pp. 1577–1604). Berlin, Heidelberg: Springer. ISBN 978-3-319-32550-7 (Part F, Chapter 60).

    Google Scholar 

  • Musić, S., & Hirche, S. (2016). Classification of human-robot team interaction paradigms. IFAC-PapersOnLine, 49–32, 042–047.

    Google Scholar 

  • Mutlu, B., Roy, N., & Šabanović, S. (2016). Cognitive human-robot interaction. In B. Siciliano & O. Khatib (Eds.), Handbook of robotics (2nd ed., pp. 1907–1933). Berlin, Heidelberg: Springer. ISBN 978-3-319-32550-7 (Part G, Chapter 71).

    Google Scholar 

  • Nagarkatti, S. P., & Dawson, D. M. (2005). Force/impedance control for robotic manipulators. In T. R. Kurfess (Ed.), Robotics and automation handbook (pp. 325–343). USA: CRC Press LLC. ISBN 0-8493-1804-1 (Chapter 16).

    Google Scholar 

  • Nardi, D., Roberts, J., Veloso, M., & Fletcher, L. (2016). Robotics competitions and challenges. In B. Siciliano & O. Khatib (Eds.), Handbook of robotics (2nd ed., pp. 1759–1783). Berlin, Heidelberg: Springer. ISBN 978-3-319-32550-7 (Part F, Chapter 66).

    Google Scholar 

  • Nolfi, S., Bongard, J., Husbands, P., & Floreano, D. (2016). Evolutionary robotics. In B. Siciliano & O. Khatib (Eds.), Handbook of robotics (2nd ed., pp. 2035–2067). Berlin, Heidelberg: Springer. ISBN 978-3-319-32550-7 (Part G, Chapter 76).

    Google Scholar 

  • Pellegrinelli, S., Orlandini, A., Pedrocchi, N., Umbrico, A., & Tolio, T. (in press). Motion planning and scheduling for human and industrial-robot collaboration. CIRP Annals—Manufacturing Technology. http://dx.doi.org/10.1016/j.cirp.2017.04.095.

  • Pellegrinelli, S., Pedrocchi, N., Tosatti, L. M., Fischer, A., & Tolio, T. (2017). Multi-robot spot-welding cells for car-body assembly: Design and motion planning. Robotics and Computer-Integrated Manufacturing, 44, 97–116.

    Article  Google Scholar 

  • Penders, J., Alboul, L., Witkowski, U., Naghsh, A., Saez-Pons, J., Herbrechtsmeier, S., et al. (2011). A robot swarm assisting a human fire-fighter. Advanced Robotics, 25, 93–117.

    Article  Google Scholar 

  • PHRIENDS. (2006-2009). Physical human-robot interaction: Dependability and safety. Project supported by the European Commission under the 6th Framework Programme (STReP IST-045359).

    Google Scholar 

  • Pinillos, R., Marcos, S., Feliz, R., Zalama, E., & Gómez-García-Bermejo, J. (2016). Long-term assessment of a service robot in a hotel environment. Robotics and Autonomous Systems, 79, 40–57.

    Article  Google Scholar 

  • Prassler, E., Munich, M. E., Pirjanian, P., & Kosuge, K. (2016). Domestic robotics. In B. Siciliano & O. Khatib (Eds.), Handbook of robotics (2nd ed., pp. 1729–1758). Berlin, Heidelberg: Springer. ISBN 978-3-319-32550-7 (Part F, Chapter 65).

    Google Scholar 

  • Quan, W., Niwa, H., Ishikawa, N., Kobayashi, Y., & Kuno, Y. (2011). Assisted-care robot based on sociological interaction analysis. Computers in Human Behavior, 27, 1527–1534.

    Article  Google Scholar 

  • Rabbitt, S. M., Kazdin, A. E., & Scassellati, B. (2015). Integrating socially assistive robotics into mental healthcare interventions: applications and recommendations for expanded use. Clinical Psychology Review, 35, 35–46.

    Article  Google Scholar 

  • Ran, C. (2015, December 3). A machine’s soul: A startup introduces robotic-assisted rehabilitation for children with autism. Beijing Review, p. 21.

    Google Scholar 

  • ROBOT-PARTNER. (2013–2016). Seamless human-robot cooperation for intelligent, flexible and safe operations in the assembly factories of the future. Project supported by the European Commission under the 7th Framework Programme. http://www.robo-partner.eu/.

  • Ros, R., Baroni, I., & Demiris, Y. (2014). Adaptive human–robot interaction in sensorimotor task instruction: from human to robot dance tutors. Robotics and Autonomous Systems, 62, 707–720.

    Article  Google Scholar 

  • Rovira-Más, F., Chatterjee, I., & Sáiz-Rubio, V. (in press). The role of GNSS in the navigation strategies of cost-effective agricultural robots. Computers and Electronics in Agriculture. http://dx.doi.org/10.1016/j.compag.2014.12.017.

  • SAFROS. (2009–2013). Patient safety in robotic surgery. Project supported by the European Commission under the 7th Framework Programme. http://www.safros.eu/safros/.

  • Saidi, K. S., Bock, T., & Georgoulas, C. (2016). Robotics in construction. In B. Siciliano & O. Khatib (Eds.), Handbook of robotics (2nd ed., pp. 1493–1519). Berlin, Heidelberg: Springer. ISBN 978-3-319-32550-7 (Part F, Chapter 57).

    Google Scholar 

  • Santis, A. D., Siciliano, B., Luca, A. D., & Bicchi, A. (2008). An atlas of physical human–robot interaction. Mechanism and Machine Theory, 43, 253–270.

    Article  MATH  Google Scholar 

  • SAPHARI. (2011-2015). Safe and autonomous physical human-aware robot interaction. Project supported by the European Commission under the 7th Framework Programme. http://www.saphari.eu.

  • Scarfogliero, U., Stefanini, C., & Dario, P. (2009). The use of compliant joints and elastic energy storage in bio-inspired legged robots. Mechanism and Machine Theory, 44, 580–590.

    Article  MATH  Google Scholar 

  • Schmickl, T., Thenius, R., Moeslinger, C., Radspieler, G., Kernbach, S., Szymanski, M., et al. (2009). Get in touch: Cooperative decision making based on robot-to-robot collisions. Autonomous Agents and Multi-Agent Systems, 18, 133–155.

    Article  Google Scholar 

  • Schneider, S., Goerlich, M., & Kummert, F. (2017). A framework for designing socially assistive robot interactions. Cognitive Systems Research, 43, 301–312.

    Article  Google Scholar 

  • Schupak, A. (2013, January). Roach control Popular Science USA, 64.

    Google Scholar 

  • Sekmen, A., & Challa, P. (2013). Assessment of adaptive human–robot interactions. Knowledge-Based Systems, 42, 49–59.

    Article  Google Scholar 

  • Senft, E., Baxter, P., Kennedy, J., Lemaignan, S., & Belpaeme, T. (in press). Supervised autonomy for online learning in human-robot interaction. Pattern Recognition Letters. http://dx.doi.org/10.1016/j.patrec.2017.03.015.

  • Shahid, S., Krahmer, E., & Swerts, M. (2014). Child–robot interaction across cultures: How does playing a game with a social robot compare to playing a game alone or with a friend? Computers in Human Behavior, 40, 86–100.

    Article  Google Scholar 

  • Shao, J., Wang, L., & Yu, J. (2008). Development of an artificial fish-like robot and its application in cooperative transportation. Control Engineering Practice, 16, 569–584.

    Article  Google Scholar 

  • Sheridan, T. B. (2016). Human–robot interaction: Status and challenges. Human Factors, 58(4), 525–532.

    Article  Google Scholar 

  • Siciliano, B., & Khatib, O. (2008). Handbook of robotics. Berlin, Heidelberg: Springer. ISBN 978-3-540-23957-4.

    Google Scholar 

  • Siciliano, B., & Khatib, O. (2016). Handbook of robotics (2nd ed.). Berlin, Heidelberg: Springer. ISBN 978-3-319-32550-7.

    Google Scholar 

  • Sim, D. Y. Y., & Loo, C. K. (2015). Extensive assessment and evaluation methodologies on assistive social robots for modelling human–robot interaction—A review. Information Sciences, 301, 305–344.

    Article  Google Scholar 

  • Sisbot, E. A., & Alami, R. (2012). A human-aware manipulation planner. IEEE Transactions on Robotics, 28(5), 1045–1057.

    Article  Google Scholar 

  • Sorbello, R., Chella, A., Calí, C., Giardina, M., Nishio, S., & Ishiguro, H. (2014). Telenoid android robot as an embodied perceptual social regulation medium engaging natural human–humanoid interaction. Robotics and Autonomous Systems, 62, 1329–1341.

    Article  Google Scholar 

  • Suchman, L. A. (1987). Plans and situated actions: The problem of human-machine communication. Cambridge: Cambridge University Press. ISBN 0-521-33137-4.

    Google Scholar 

  • Suhadolnik, N., Galimberti, J., & Silva, S. D. (2010). Robot traders can prevent extreme events in complex stock markets. Physica A: Statistical Mechanics and its Applications, 389, 5182–5192.

    Article  Google Scholar 

  • Sumiya, T., Matsubara, Y., Nakano, M., & Sugaya, M. (2015). A mobile robot for fall detection for elderly-care. Procedia Computer Science, 60, 870–880.

    Article  Google Scholar 

  • Tang, X., & Yamada, H. (2011). Tele-operation construction robot control system with virtual reality technology. Procedia Engineering, 15, 1071–1076.

    Article  Google Scholar 

  • Tapus, A., & Matarić, M. J. (2006). Towards socially assistive robotics. International Journal of the Robotics Society of Japan, 24(5), 1–3.

    Google Scholar 

  • Tay, B., Jung, Y., & Park, T. (2014). When stereotypes meet robots: The double-edge sword of robot gender and personality in human–robot interaction. Computers in Human Behavior, 38, 75–84.

    Article  Google Scholar 

  • Taylor, R. H., Menciassi, A., Fichtinger, G., Fiorini, P., & Dario, P. (2016). Medical robotics and computer-integrated surgery. In B. Siciliano & O. Khatib (Eds.), Handbook of robotics (2nd ed., pp. 1657–1683). Berlin, Heidelberg: Springer. ISBN 978-3-319-32550-7 (Part F, Chapter 63).

    Google Scholar 

  • Thobbi, A., Gu, Y., & Sheng, W. (2011). Using human motion estimation for human-robot cooperative manipulation. Paper presented at the Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), September 25–30, 2011, San Francisco, California, USA, pp. 2873–2878.

    Google Scholar 

  • Toda, Y., & kubota, N. (2013). Attention allocation for multi-modal perception of human-friendly robot partners. Paper presented at the Proceedings of the 12th IFAC Symposium on Analysis, Design, and Evaluation of Human-Machine Systems, August 11–15, 2013. Las Vegas, NV, USA, pp. 324–329.

    Google Scholar 

  • Trafton, J. G., Schultz, A. C., Cassimatis, N. L., Hiatt, L. M., Perzanowski, D., Brock, D. P., … Adams, W. (2006). Communicating and collaborating with robotic agents. In R. Sun (Ed.), Cognition and multi-agent interaction: From cognitive modeling to social simulation (pp. 252–278). New York, USA: Cambridge University Press. ISBN -13 978-0-521-83964-8.

    Google Scholar 

  • Trevelyan, J., Hamel, W. R., & Kang, S.-C. (2016). Robotics in hazardous applications. In B. Siciliano & O. Khatib (Eds.), Handbook of robotics (2nd ed., pp. 1521–1548). Berlin, Heidelberg: Springer. ISBN 978-3-319-32550-7 (Part F, Chapter 58).

    Google Scholar 

  • Tsagarakis, N. G., & Caldwell, N. G. (2003). Development and control of a ‘soft-actuated’ exoskeleton for use in physiotherapy and training. Autonomous Robots, 15, 21–23.

    Article  Google Scholar 

  • Tzafestas, S. G. (2016). An introduction to robophilosoph: Cognition, intelligence, autonomy, consciousness, conscience, and ethics. Denmark: River Publishers.

    Google Scholar 

  • Van der Loos, H. F. M., Reinkensmeyer, D. J., & Guglielmelli, E. (2016). Rehabilitation and health care robotics. In B. Siciliano & O. Khatib (Eds.), Handbook of robotics (2nd ed., pp. 1685–1728). Berlin, Heidelberg: Springer. ISBN 978-3-319-32550-7 (Part F, Chapter 64).

    Google Scholar 

  • van der Smagt, P., Arbib, M. A., & Metta, G. (2016). Neurorobotics: From vision to action. In B. Siciliano & O. Khatib (Eds.), Handbook of robotics (2nd ed., pp. 2069–2094). Berlin, Heidelberg: Springer. ISBN 978-3-319-32550-7 (Part G, Chapter 77).

    Google Scholar 

  • Vanderborght, B., Albu-Schäffer, A., Bicchi, A., Burdet, E., Caldwell, D. G., Carloni, R., et al. (2013). Variable impedance actuators: A review. Robotics and Autonomous Systems, 61(12), 1601–1614.

    Article  Google Scholar 

  • Vera, A. H., & Simon, H. A. (1993). Situated action: A symbolic interpretation. Cognitive Science, 17(1), 7–48.

    Article  Google Scholar 

  • Veruggio, G., Operto, F., & Bekey, G. (2016). Roboethics: Social and ethical implications. In B. Siciliano & O. Khatib (Eds.), Handbook of robotics (2nd ed., pp. 2135–2160). Berlin, Heidelberg: Springer. ISBN 978-3-319-32550-7 (Part G, Chapter 80).

    Google Scholar 

  • Wang, X. V., Kemény, Z., Váncza, J., & Wang, L. (in press). Human–robot collaborative assembly in cyber-physical production: Classification framework and implementation. CIRP Annals—Manufacturing Technology. http://dx.doi.org/10.1016/j.cirp.2017.04.101.

  • Wei, H., Li, N., Liu, M., & Tan, J. (2013). A novel autonomous self-assembly distributed swarm flying robot. Chinese Journal of Aeronautics, 26(3), 791–800.

    Article  Google Scholar 

  • Westlund, J. M. K., Dickens, L., Jeong, S., Harris, P. L., DeSteno, D., & Breazeal, C. L. (in press). Children use non-verbal cues to learn new words from robots as well as people. International Journal of Child-Computer Interaction. http://dx.doi.org/10.1016/j.ijcci.2017.04.001.

  • Winograd, T., & Flores, F. (1986). Understanding computers and cognition: a new foundation for design. USA: Ablex Publishing Corporation. ISBN 0-89391-050-3.

    Google Scholar 

  • Wolf, A., Choset, H. H., Brown, B. H., & Casciola, R. W. (2005). Design and control of a mobile hyper-redundant urban search and rescue robot. Advanced Robotics, 19(3), 221–248.

    Article  Google Scholar 

  • Yamane, K., & Takano, W. (2016). Human motion reconstruction. In B. Siciliano & O. Khatib (Eds.), Handbook of robotics (2nd ed., pp. 1819–1833). Berlin, Heidelberg: Springer. ISBN 978-3-319-32550-7 (Part G, Chapter 68).

    Google Scholar 

  • Yamazaki, A., Yamazaki, K., Burdelski, M., Kuno, Y., & Fukushima, M. (2010). Coordination of verbal and non-verbal actions in human–robot interaction at museums and exhibitions. Journal of Pragmatics, 42, 2398–2414.

    Article  Google Scholar 

  • Yoshida, K., Wilcox, B., Hirzinger, G., & Lampariello, R. (2016). Space robotics. In B. Siciliano & O. Khatib (Eds.), Handbook of robotics (2nd ed., pp. 1423–1461). Berlin, Heidelberg: Springer. ISBN 978-3-319-32550-7 (Part F, Chapter 54).

    Google Scholar 

  • Yu, H., Huang, S., Chen, G., & Thakor, N. (2013). Control design of a novel compliant actuator for rehabilitation robots. Mechatronics, 23, 1072–1083.

    Article  Google Scholar 

  • Zaier, R. (Ed.). (2011). The future of humanoid robots—research and applications. Croatia: InTech. ISBN 978-953-307-951-6.

    Google Scholar 

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  1. Faculty of Engineering and the Built Environment, Institute for Intelligent System, University of Johannesburg, Johannesburg, South Africa

    Bo Xing

  2. Faculty of Engineering and the Built Environment, Department of Electrical and Electronic Engineering Sciences, University of Johannesburg, Johannesburg, South Africa

    Tshilidzi Marwala

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Xing, B., Marwala, T. (2018). Introduction to Human Robot Interaction. In: Smart Maintenance for Human–Robot Interaction. Studies in Systems, Decision and Control, vol 129. Springer, Cham. https://doi.org/10.1007/978-3-319-67480-3_1

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