Minds and Machines

, Volume 29, Issue 1, pp 109–125 | Cite as

Robotic Simulations, Simulations of Robots

  • Edoardo Datteri
  • Viola SchiaffonatiEmail author


Simulation studies have been carried out in robotics for a variety of epistemic and practical purposes. Here it is argued that two broad classes of simulation studies can be identified in robotics research. The first one is exemplified by the use of robotic systems to acquire knowledge on living systems in so-called biorobotics, while the second class of studies is more distinctively connected to cases in which artificial systems are used to acquire knowledge about the behaviour of autonomous mobile robots. The two classes pertain to sub-areas of robotics which are apparently quite distant from one another in terms of goals, methodologies, technologies, and theoretical backgrounds. Still both are concerned with building, running, and experimenting on simulations of other systems. This paper aims to reveal and discuss some methodological commonalities between the two classes of studies. Philosophical literature on simulation methodologies has been traditionally focused on studies carried out in research fields other than robotics: this article may therefore contribute to shedding light on how the concept of simulation is used in robotics, and on the role simulation methodologies play in this research field.


Robotic simulation Simulation system Biorobotics Autonomous robotics 



  1. Ambros-Ingerson, J., Granger, R., & Lynch, G. (1990). Simulation of paleocortex performs hierarchical clustering. Science, 247(4948), 1344–1348.CrossRefGoogle Scholar
  2. Arkin, R. C. (1998). Behavior-based robotics. Cambridge: The MIT Press.Google Scholar
  3. Balakirsky, S., Carpin, S., Kleiner, A., Lewis, M., Visser, A., Wang, J., et al. (2007). Towards heterogeneous robot teams for disaster mitigation: Results and performance metrics from Robocup rescue. Journal of Field Robotics, 24(11), 943–967.CrossRefGoogle Scholar
  4. Barberousse, A., Franceschelli, S., & Imbert, C. (2009). Computer simulations as experiments. Synthese, 169(3), 557–574.MathSciNetCrossRefGoogle Scholar
  5. Beisbart, C. (2018). Are computer simulations experiments? And if not, how are they related to each other? European Journal for Philosophy of Science, 8(2), 171–204.MathSciNetCrossRefGoogle Scholar
  6. Blanchard, M., Rind, F. C., & Verschure, P. F. M. J. (2000). Collision avoidance using a model of the locust LGMD neuron. Robotics and Autonomous Systems, 30(1–2), 17–38.CrossRefGoogle Scholar
  7. Bokulich, A. (2017). Models and Explanation. In L. Magnani & T. Bertolotti (Eds.), Springer handbook of model-based science (pp. 103–118). New York and Cham: Springer.CrossRefGoogle Scholar
  8. Braitenberg, V. (1986). Vehicles. Experiments in synthetic psychology. Cambridge: The MIT Press.Google Scholar
  9. Cheah, C. C., Hou, S. P., & Slotine, J. J. (2009). Region-based shape control for a swarm of robots. Automatica, 45(10), 2406–2411.MathSciNetCrossRefzbMATHGoogle Scholar
  10. Cordeschi, R. (2002). The discovery of the artificial. Behavior, mind and machines before and beyond cybernetics. Dordrecht: Springer.Google Scholar
  11. Craver, C. F. (2006). When mechanistic models explain. Synthese, 153(3), 355–376.MathSciNetCrossRefGoogle Scholar
  12. Datteri, E. (2017). The epistemic value of brain–machine systems for the study of the brain. Minds and Machines, 27(2), 287–313.CrossRefGoogle Scholar
  13. Datteri, E., & Tamburrini, G. (2007). Biorobotic experiments for the discovery of biological mechanisms. Philosophy of Science, 74(3), 409–430.CrossRefGoogle Scholar
  14. Dror, R. O., Dirks, R. M., Grossman, J. P., Xu, H., & Shaw, D. E. (2012). Biomolecular simulation: A computational microscope for molecular biology. Annual Review of Biophysics, 41(1), 429–452.CrossRefGoogle Scholar
  15. Feigenbaum, E. (1961). The simulation of verbal learning behavior. In Papers presented at the May 9–11, 1961, Western joint IRE-AIEE-ACM computer conference, pp. 121–132.Google Scholar
  16. Frigg, R., & Nguyen, J. (2017). Models and representation. Springer handbook of model-based science (pp. 49–102). Cham: Springer.CrossRefGoogle Scholar
  17. Glennan, S. (2017). The new mechanical philosophy. Oxford: Oxford University Press.CrossRefGoogle Scholar
  18. Grasso, F. W., Consi, T. R., Mountain, D. C., & Atema, J. (2000). Biomimetic robot lobster performs chemo-orientation in turbulence using a pair of spatially separated sensors: Progress and challenges. Robotics and Autonomous Systems, 30(1–2), 115–131.CrossRefGoogle Scholar
  19. Guala, F. (2002). Models, Simulations, and Experiments. In L. Magnani & N. J. Nersessian (Eds.), Model-based reasoning. Science, technology, values (pp. 59–74). New York: Springer US.Google Scholar
  20. Hartmann, S. (1996). The world as a process: simulations in the natural and social sciences. In R. Hegselmann, et al. (Eds.), Simulation and modeling in the social sciences from the philosophy of science point of view (pp. 77–100). Dordrecht: Theory and Decision Library, Kluwer.Google Scholar
  21. Humphreys, P. (2004). Extending ourselves: Computational science, empiricism, and scientific method. New York: Oxford University Press.CrossRefGoogle Scholar
  22. Jennings, J. S., Orleans, N., Whelan, G., & Evans, W. F. (1997). Cooperative search and rescue with a team of mobile robots. In Proceedings of the IEEE Int. Conf. on Advanced Robotics (ICAR), (pp. 193–200).Google Scholar
  23. Kleiner, A., Prediger, J., & Nebel, B. (2006). RFID Technology-based exploration and SLAM for search and rescue. In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), (pp. 4054–4059).Google Scholar
  24. Long, J. (2012). Darwin’s Devices. What evolving robots can teach us about the history of life and the future of technology. New York: Basic Books.Google Scholar
  25. Long, J. H., Schumacher, J., Livingston, N., & Kemp, M. (2006). Four flippers or two? Tetrapodal swimming with an aquatic robot. Bioinspiration & Biomimetics, 1(1), 20–29.CrossRefGoogle Scholar
  26. Pfeifer, R. (2009). Biologically inspired robotics. Science, 1088 (2007).Google Scholar
  27. Rosenblueth, A., & Wiener, N. (1945). The role of models in science. Philosophy of Science, 12(4), 316–321.CrossRefGoogle Scholar
  28. Siciliano, B., & Khatib, O. (Eds.). (2008). Springer handbook of robotics. Heidelberg: Springer.zbMATHGoogle Scholar
  29. Simon, H. A., & Newell, A. (1962). Computer simulation of human thinking and problem solving. Monographs of the Society for Research in Child Development, 27(2), 137.CrossRefGoogle Scholar
  30. Suppe, F. (1989). The semantic conception of theories and scientific realism. Urbana and Chicago: University of Illinois Press.Google Scholar
  31. Swoyer, C. (1991). Structural representation and surrogative reasoning. Synthese, 87(3), 449–508.MathSciNetCrossRefGoogle Scholar
  32. Tamburrini, G., & Datteri, E. (2005). Machine experiments and theoretical modelling: From cybernetic methodology to neuro-robotics. Minds and Machines, 15(3–4), 335–358.CrossRefGoogle Scholar
  33. Webb, B. (2001). Can robots make good models of biological behaviour? The Behavioral and Brain Sciences, 24(6), 1033–1050–1094.Google Scholar
  34. Webb, B. (2006). Validating biorobotic models. Journal of Neural Engineering, 3, R25–R35.CrossRefGoogle Scholar
  35. Weisberg, M. (2013). Simulation and similarity. using models to understand the world. Oxford: Oxford University Press.CrossRefGoogle Scholar
  36. Winsberg, E. (1999). Sanctioning models: The epistemology of simulation. Science in Context, 12(2), 275–292.CrossRefGoogle Scholar
  37. Ziemke, T. (2003). On the role of robot simulations in embodied cognitive science. AISB Journal, 1(4), 389–399.Google Scholar

Copyright information

© Springer Nature B.V. 2019

Authors and Affiliations

  1. 1.RobotiCSS Lab, Laboratory of Robotics for the Cognitive and Social Sciences, Department of Human Sciences for EducationUniversità degli Studi di Milano-BicoccaMilanItaly
  2. 2.Artificial Intelligence and Robotics Laboratory, Department of Electronics, Information, and BioengineeringPolitecnico di MilanoMilanItaly

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