Morphogenetic robotics

Morphogenetic robotics [1] generally refers to the methodologies that address challenges in robotics inspired by biological morphogenesis.[2][3]

Contents

Background

Differences to epigenetic

Morphogenetic robotics is related to, but differs from, epigenetic robotics. The main difference between morphogenetic robotics and epigenetic robotics is that the former focuses on self-organization, self-reconfiguration, self-assembly and self-adaptive control of robots using genetic and cellular mechanisms inspired from biological early morphogenesis (activity-independent development), during which the body and controller of the organisms are developed simultaneously, whereas the latter emphasizes the development of robots' cognitive capabilities, such as language, emotion and social skills, through experience during the lifetime (activity-dependent development). Morphogenetic robotics is closely connected to developmental biology and systems biology, whilst epigenetic robotics is related to developmental cognitive neuroscience emerged from cognitive science, developmental psychology and neuroscience.

Topics

Morphogenetic robotics includes, but is not limited to the following main topics:

See also

References

  1. ^ Y. Jin and Y. Meng. Morphogenetic robotics: An emerging new field in developmental robotics. IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews, 41(2):145-160, 2011
  2. ^ I. Salazar-Ciudad, H. Garcia-Fernandez, and R. V. Sole. Gene networks capable of pattern formation: from induction to reaction-diffusion. Journal of Theoretical Biology, 205:587-603, 2000
  3. ^ L. Wolpert. Principles of Development. Oxford University Press, 2002
  4. ^ H. Guo, Y. Meng, and Y. Jin. A cellular mechanism for multi-robot construction via evolutionary multi-objective optimization of a gene regulatory network. BioSystems, 98(3):193-203, 2009
  5. ^ M. Mamei, M. Vasirani, F. Zambonelli, Experiments in morphogenesis in swarms of simple mobile robots. Applied Artificial Intelligence, 18, 9-10: 903-919, 2004
  6. ^ W. Shen, P. Will and A. Galstyan. Hormone-inspired self-organization and distributed control of robotic swarms. Autonomous Robots, 17, pp.93-105, 2004
  7. ^ H. Hamann, H. Wörn, K. Crailsheim, T. Schmickl: Spatial macroscopic models of a bio-inspired robotic swarm algorithm. IROS 2008: 1415-1420
  8. ^ T. Schmickl, J. Stradner, H. Hamann, and K. Crailsheim. Major Feedbacks that Support Artificial Evolution in Multi-Modular Robotics. Proc. IEEE/RSJ Int. Conf. Intelligent Robots and Systems (IROS), Exploring New Horizons in Evolutionary Design of Robots Workshop, Oct. 11-15 2009, St. Louis, MO, USA, pp. 65-72
  9. ^ Y. Meng, Y. Zheng and Y. Jin. Autonomous self-reconfiguration of modular robots by evolving a hierarchical mechnochemical model. IEEE Computational Intelligence Magazine, 6(1):43-54, 2011
  10. ^ G.S. Hornby and J.B. Pollack. Body-brain co-evolution using L-systems as a generative encoding. Artificial Life, 8:3, 2002
  11. ^ J.A. Lee and J. Sitte. Morphogenetic Evolvable Hardware Controllers for Robot Walking. In: 2nd International Symposium on Autonomous Minirobots for Research and Edutainment (AMiRE 2003), Feb. 18-20, 2003, Brisbane, Australia
  12. ^ G. Gomez and P. Eggenberger. Evolutionary synthesis of grasping through self-exploratory movements of a robotic hand. Congress on Evolutionary Computation, 2007
  13. ^ L. Schramm, Y. Jin, B. Sendhoff. Emerged coupling of motor control and morphological development in evolution of multi-cellular animates. 10th European Conference on Artificial Life, Budapest, September 2009

External links