Skip to main content

Part of the book series: Technik im Fokus ((TECHNIK))

  • 2059 Accesses

Abstract

With the increasing complexity and automation of technology, robots are becoming service providers for industrial society. The evolution of living organisms today inspires the construction of robotic systems for different purposes [1]. As the complexity and difficulty of the service task increases, the use of AI technology becomes unavoidable. And robots don’t have to look like humans. Just as airplanes do not look like birds, there are also other adapted shapes depending on their function. So the question arises for what purpose humanoid robots should possess which properties and abilities.

Humanoid robots should be able to act directly in the human environment. In the human environment, the environment is adapted to human proportions. The design ranges from the width of the corridors and the height of a stair step to the positions of door handles. For non-human robots (e.g. on wheels and with other grippers instead of hands) large investments for environmental changes would have to be made. In addition, all tools that humans and robots should use together are adapted to human needs. Not to be underestimated is the experience that humanoid forms psychologically facilitate the emotional handling of robots.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

eBook
USD 24.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 32.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Mainzer K (2010) Leben als Maschine? Von der Systembiologie zur Robotik und künstlichen Intelligenz. Mentis, Paderborn

    Google Scholar 

  2. Kajita S (ed) (2007) Humanoide Roboter. Theorie und Technik des Künstlichen Menschen. Aka, Berlin

    Google Scholar 

  3. Ulbrich H, Buschmann T, Lohmeier S (2006) Development of the humanoid robot LOLA. J Appl Mech Mater 5(6):529–539

    Article  Google Scholar 

  4. Murray RM, Li Z, Sastry SS (1994) A mathematical introduction to robot manipulation. CRC Press, Boca Raton

    Google Scholar 

  5. Isozumi Akaike, Hirata Kaneko, Kajita Hiruka (2004) Development of humanoid robot HRP-2. J RSJ 22(8):1004–1012

    Google Scholar 

  6. Newell A, Simon HA (1972) Human problem solving. Prentice Hall, Englewood Cliffs

    Google Scholar 

  7. Siegert H, Norvig P (1996) Robotik: Programmierung intelligenter Roboter. Springer, Berlin

    Book  Google Scholar 

  8. Valera F, Thompson E, Rosch E (1991) The embodied mind. Cognitive science and human experience. MIT Press, Cambridge

    Google Scholar 

  9. Marcus G (2003) The algebraic mind: integrating connectionism and cognitive science. MIT Press, Cambridge

    Google Scholar 

  10. Pfeifer R, Scheier C (2001) Understanding intelligence. A Bradford Book, Cambridge

    Book  Google Scholar 

  11. Mainzer K (2009) From embodied mind to embodied robotics: humanities and system theoretical aspects. J Physiol (Paris) 103:296–304

    Article  Google Scholar 

  12. Domingos P, Richardson M (2004) Markov logic: a unifying framework for statistical relational learning. In: Proceedings of the ICML Workshop on Statistical Relational Learning and Its Connections to Other Fields, S 49–54

    Google Scholar 

  13. Koerding KP, Wolpert D (2006) Bayesian decision theory in sensomotor control. Trends in Cogn Sci 10:319–329

    Article  Google Scholar 

  14. Thurn S, Burgard W, Fox D (2005) Probabilistic robotics. MIT Press, Cambridge

    Google Scholar 

  15. Pearl J (2000) Causality, models, reasoning, and inference. Cambridge University Press, Cambridge

    Google Scholar 

  16. Glymour C, Scheines R, Spirtes P, Kelley K (1987) Discovering causal structures. Artificial intelligence, philosophy of science, and statistical modeling. Academic Press, Orlando

    Google Scholar 

  17. Braitenberg V (1986) Künstliche Wesen. Verhalten kybernetischer Vehikel. Vieweg + Teubner, Braunschweig

    Book  Google Scholar 

  18. Arkin R (1998) Behavior-based robotics. A Bradford Book, Cambridge

    Google Scholar 

  19. Knoll A, Christaller T (2003) Robotik. Fischer Taschenbuch, Frankfurt, S 82 (nach Abb. 17)

    Google Scholar 

  20. Wilson EO (2000) Sociobiology: the new synthesis, 25th Anniversary Edition. Belknap Press, Cambridge

    Book  Google Scholar 

  21. Wilson EO (1971) The insect societies. Belknap Press, Cambridge

    Google Scholar 

  22. Balch T, Parker L (eds) (2002) Robot teams: from diversity to polymorphism. A K Peters/CRC Press, Wellesley

    Google Scholar 

  23. Mataric M (1993) Designing emergent behavior: from local interaction to collective intelligence. In: From Animals to Animates 2 2nd Intern. Conference on Simulation of Adaptive Behavior, S 432–441

    Google Scholar 

  24. Mataric M, Sukhatme G, Ostergaard E (2003) Multi-robot task allocation in uncertain environments. Autonomous Robots 14(2–3):253–261

    Google Scholar 

  25. Brooks RA (2005) Menschmaschinen. Campus Sachbuch, Frankfurt

    Google Scholar 

  26. Dautenhahn K (1995) Getting to know each other—articial social intelligence for autonomous robots. Robotics and Autonomous Systems 16:333–356

    Article  Google Scholar 

  27. Stone P (2000) Layered learning in multiagent systems. A winning approach to robotic soccer. A Bradford Book, Cambridge

    Book  Google Scholar 

  28. Leottau DL, Ruiz-del-Solar J, MacAlpine P, Stone P (2016) A study of layered learning strategies applied to individual behaviors in robot soccer. In: Almeida L, Ji J, Steinbauer G, Luke S (eds) RoboCup-2015: robot soccer world cup XIX, lecture notes in artificial intelligence. Springer, Berlin

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Klaus Mainzer .

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer-Verlag GmbH Germany, part of Springer Nature

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Mainzer, K. (2020). Robots Become Social. In: Artificial intelligence - When do machines take over?. Technik im Fokus. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-59717-0_8

Download citation

  • DOI: https://doi.org/10.1007/978-3-662-59717-0_8

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-662-59716-3

  • Online ISBN: 978-3-662-59717-0

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics