Modelling a hormone-inspired controller for individual- and multi-modular robotic systems

Mathematical and Computer Modelling of Dynamical Systems

Volumn 17, Issue 3, 2011, Pages 221-242

  Schmickl, Thomas ^a   Hamann, Heiko ^a   Crailsheim, Karl ^a  

^a UNIVERSITY OF GRAZ   (Austria)

Author keywords

Cybernetics; Homeostasis; Hormone controller; Modular robotics; Stock and flow modelling; System dynamics

Indexed keywords

EID: 79957619673     PISSN: 13873954     EISSN: 17445051     Source Type: Journal    
DOI: 10.1080/13873954.2011.557862     Document Type: Article

References (50)

1. G. Beni, From swarm intelligence to swarm robotics, in Proceedings of the SAB 2004 Workshop on Swarm Robotics, Lecture Notes in Computer Science, E. Şahin andW.M. Spears, eds., Santa Monica, CA, July 2004, pp. 1-9.
2. E. Bonabeau, M. Dorigo, and G. Theraulaz, Swarm Intelligence: From Natural to Artificial Systems, Oxford University Press, New York, 1999.
3. E. Şahin, Swarm robotics: From sources of inspiration to domains of application, in Swarm Robotics Workshop: State-of-the-Art Survey. Volume 3342: LNCS, E. Şahin and W.M. Spears, eds., Springer-Verlag, Berlin, Heidelberg, 2005, pp. 10-20.
4. J. Kennedy and R.C. Eberhart, Swarm Intelligence, Morgan Kaufmann, San Francisco, CA, 2001.
5. P. Corradi, T. Schmickl, O. Scholz, A. Menciassi, and P. Dario, Optical networking in a swarm of microrobots, Lect. Notes Inst. Comput. Sci., Soc. Inform. Telecommun. Eng., 3 (2) (2009), 107-119.
6. J. Seyfried, M. Szymanski, N. Bender, R. Estaña, M. Thiel, and H. Wörn, The I-SWARM project: Intelligent small world autonomous robots for micro-manipulation, in Swarm Robotics Workshop: State-of-the-art Survey, E. Şahin and W.M. Spears, eds., Springer-Verlag, Berlin, Heidelberg, 2005, pp. 70-83.
7. P. Valdastri, P. Corradi, A. Menciassi, T. Schmickl, K. Crailsheim, J. Seyfried, and P. Dario, Micromanipulation, communication and swarm intelligence issues in a swarm microrobotic platform, Rob. Auton. Syst. 54 (2006), 789-804.
8. H. Hamann and H. Wörn, A Space- and Time-Continuous Model of Self-Organizing Robot Swarms for Design Support, First IEEE International Conference on Self-Adaptive and Self- Organizing Systems (SASO'07), Boston, MA, 9-11 July, IEEE Press, Los Alamitos, CA, July 2007, pp. 23-31.
9. T. Schmickl and K. Crailsheim, Trophallaxis Among Swarm-Robots: A Biologically Inspired Strategy for Swarm Robotics, Proceedings of the 1st IEEE/RAS-EMBS International Conference on Biomedical Robotics and Biomechanotronics, Pisa, Italy, 20-22 February 2006.
10. T. Schmickl and K. Crailsheim, Trophallaxis within a robotic swarm: Bio-inspired communication among robots in a swarm, Auton. Rob. 25 (1-2) (2008), 171-188.
11. J.H. Holland, Adaptation in Natural and Artificial Systems, University of Michigan Press, Ann Arbor, MI, 1975.
12. J. Koza, Genetic Programming: On the Programming of Computers by Means of Natural Selection, MIT Press, Cambridge, MA, 1992.
13. I. Rechenberg, Evolutionsstrategie'94, Frommann Holzboog, Stuttgart, 1994.
14. H.-P. Schwefel, Evolution and Optimum Seeking, Wiley & Sons, New York, 1995.
15. T. Schmickl, Ch. Möslinger, R. Thenius, and K. Crailsheim, Bio-inspired navigation of autonomous robots in heterogenous environments, Int. J. Factory Autom. Rob. Soft Comput. 3 (2007), 164-170.
16. T. Schmickl, Ch. Möslinger, R. Thenius, and K. Crailsheim, Individual adaptation allows collective path-finding in a robotic swarm, Int. J. Factory Autom., Rob. Soft Comput. 4 (2007), 102-108.
17. SYMBRION, Project website, 2010. Available at http://www.symbrion.eu/ (Accessed 24 February 2011).
18. REPLICATOR, Project website, 2010. Available at http://www.replicators.eu/ (Accessed 24 February 2011).
19. Swarm Robot, Project website, 2007. Available at http://www.swarmrobot.org/ (Accessed 24 February 2011).
20. J.W. Forrester, World Dynamics. Wright-Allen, Cambridge, MA, 1971.
21. L. Winkler and H. Wörn, Symbricator3D - A distributed simulation environment for modular robots, in ICIRA. Volume 5928: LNCS, M. Xie, Y. Xiong, C. Xiong, H. Liu, and Z. Hu, eds., Springer-Verlag, Berlin, Heidelberg, 2009, pp. 1266-1277.
22. F. Mondada, M. Bonani, X. Raemy, J. Pugh, C. Cianci, A. Klaptocz, S. Magnenat, J.-C. Zufferey, D. Floreano, and A. Martinoli, The e-Puck, a Robot Designed for Education in Engineering, Proceedings of the 9th Conference on Autonomous Robot Systems and Competitions, Castelo Branco, Portugal, 6-10 May 2009, Vol. 1, pp. 59-65.
23. T. Schmickl, H. Hamann, J. Stradner, and K. Crailsheim, Hormone-based control for multimodular robotics, in Symbiotic Multi-Robot Organisms: Reliability, Adaptability, Evolution, P. Levi and S. Kernbach, eds., Springer-Verlag, Berlin, Heidelberg, February 2010.
24. J. Stradner, H. Hamann, T. Schmickl, R. Thenius, and K. Crailsheim, Evolving a Novel Bio- Inspired Controller in Reconfigurable Robots, 10th European Conference on Artificial Life (ECAL'09), LNCS, Springer, 2010, in press.
25. D.E. Goldberg, Genetic Algorithms in Search, Optimization, and Machine Learning. Addison- Wesley, New York, 1989.
26. O. Avila-García and L. Cañamero, Hormonal modulation of perception in motivation-based action selection architectures, in Agents thatWant and Like: Motivational and Emotional Roots of Cognition and Action, Symposium of the AISB'05 Convention, L. Cañamero, ed., University of Hertfordshire, UK, 14-15 April 2005, pp. 700-712.
27. R.C. Moioli, P.A. Vargas, and P. Husbands, A Multiple Hormone Approach to the Homeostatic Control of Conflicting Behaviours in an Autonomous Mobile Robot, Proceedings of the IEEE Congress on Evolutionary Computation, Trondheim, Norway, 2009, CEC 2009, pp. 47-54.
28. M. Neal and J. Timmis, Timidity: A useful mechanism for robot control? Informatica 4 (27) (2003), 197-204.
29. S. Sugano and T. Ogata, Emotional Communication Robot: Wamoeba-2r Emotion Model and Evaluation Experiments, Proceedings of the International Conference on Humanoid Robots (Humanoids 2000), The Massachusetts Institute of Technology, Cambridge, MA, 2000.
30. P.A. Vargas, R.C. Moioli, F.J. von Zuben, and P. Husbands, Homeostasis and evolution together dealing with novelties and managing disruptions, Int. J. Intell. Comput. Cybern. 2 (3) (2009), 435-454.
31. W.-M. Shen, B. Salemi, and P. Will, Hormone-inspired adaptive communication and distributed control for CONRO self-reconfigurable robots, IEEE Trans. Rob. Autom. 18(5) (2002), 700-712.
32. D. Payton, M. Daily, R. Estowski, M. Howard, and C. Lee, Pheromone robotics, Auton. Rob., 11 (3) (November 2001), 319-324.
33. J. Stradner, H. Hamann, T. Schmickl, and K. Crailsheim, Analysis and Implementation of an Artificial Homeostatic Hormone System: A First Case Study in Robotic Hardware, The 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS'09), IEEE Press, Los Alamitos, CA, 2009, pp. 595-600.
34. H. Hamann, J. Stradner, T. Schmickl, and K. Crailsheim, Artificial hormone reaction networks: Towards higher evolvability in evolutionary multi-modular robotics, in Alife XII, H. Fellermann, M. Dörr, M.M. Hanczyc, L.L. Laursen, S. Maurer, D. Merkle, P.-A. Monnard, K. Stoy and S. Rasmussen, eds., MIT Press, Odense, Denmark, 2010, pp. 773-780.
35. H. Hamann, J. Stradner, T. Schmickl, and K. Crailsheim, A Hormone-Based Controller for Evolutionary Multi-Modular Robotics: From Single Modules to Gait Learning, Proceedings of the IEEE Congress on Evolutionary Computation (CEC'10), IEEE Press, Barcelona, Spain, 2010, pp. 224-251.
36. Ventana Systems, Vensim™, Available at http://www.vensim.com (Accessed 24 February 2011).
37. A.L. Nelson, G.J. Barlow, and L. Doitsidis, Fitness functions in evolutionary robotics: A survey and analysis, Rob. Auton. Syst. 57 (2009), 345-370.
38. J. Hallam and A.J. Ijpeert. Using evolutionary methods to parameterize neural models: A study of the lamprey central pattern generator, in Biologically Inspired Robot Behavior Engineering, Chapter 7, R.J. Duro, J. Santos, and M. Grana, eds., Physica-Verlag GmbH, Heidelberg, Germany, 2003, pp. 198-213.
39. T. Schmickl and K. Crailsheim, A navigation algorithm for swarm robotics inspired by slime mold aggregation, Lect. Notes Comput. Sci. 4433 (2007), 1-13.
40. W.-M. Shen, P. Will, A. Galstyan, and C.-M. Chuong, Hormone-inspired self-organization and distributed control of robotic swarms, Auton. Rob. 17 (2004), 93-105.
41. M. Rubenstein and W.-M. Shen, A Scalable and Distributed Model for Self-Organization and Self-Healing, Proceedings of the International Conference on Autonomous Agents and Multiagent Systems, Estoril, Portugal, May 2008.
42. M. Rubenstein and W.-M. Shen, Scalable Self-Assembly and Self-Repair in a Collective of Robots, Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), St. Louis, MO, October 2009.
43. T. Schmickl, C. Möslinger, and K. Crailsheim, Collective perception in a robot swarm, in Swarm Robotics - Second SAB 2006 International Workshop. Volume 4433: LNCS, E. Şahin, W.M. Spears, and A.F.T. Winfield, eds., Springer-Verlag, Berlin, Heidelberg, 2007.
44. M. Rubenstein, Y. Sai, C.-M. Choung, and W.-M. Shen, Regenerative patterning in swarm robots: Mutual benefits of research in robotics and stem cell biology, Int. J. Dev. Biol. 53 (2009), 869-881.
45. D. Floreano, P. Dürr, and C. Mattiussi, Neuroevolution: From architectures to learning, Evol. Intell. 1 (2008), 47-62.
46. D. Floreano, P. Husbands, and S. Nolfi, Evolutionary robotics, in Handbook of Robotics, B. Siciliano and K. Oussama, eds., Springer, Berlin, 2008, pp. 1423-1452.
47. V. Braitenberg, Vehicles: Experiments in Synthetic Psychology. MIT Press, Cambridge, MA, 1984.
48. N. Wiener, Cybernetics: or Control and Communication in the Animal and the Machine, MIT Press, Cambridge, MA, 1948.
49. J.R. Pierce, An Introduction to Information Theory. Symbols, Signals and Noise, Dover Publications, New York, 1980.
50. C.E. Shannon, A mathematical theory of communication, Bell Syst. Tech. J. 27 (July and October 1948), 79-423.