Morphogenetic robotics
Morphogenetic robotics Y. Jin and Y. Meng. [https://ieeexplore.ieee.org/xpl/tocresult.jsp?isnumber=5714230 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 generally refers to the methodologies that address challenges in robotics inspired by biological morphogenesis.I. Salazar-Ciudad, H. Garcia-Fernandez, and R. V. Sole. [https://www.sciencedirect.com/science/article/pii/S0022519300920927 Gene networks capable of pattern formation: from induction to reaction-diffusion]. Journal of Theoretical Biology, 205:587-603, 2000L. Wolpert. Principles of Development. Oxford University Press, 2002 This field overlaps with Morphogenetic Engineering that's extenuated inside Amorphous Computation.
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:
- "Morphogenetic swarm robotics" deals with the self-organization of multi-robots using genetic and cellular mechanisms governing the biological early morphogenesis;H. Guo, Y. Meng, and Y. Jin. [https://www.ncbi.nlm.nih.gov/pubmed/19446001?dopt=Abstract A cellular mechanism for multi-robot construction via evolutionary multi-objective optimization of a gene regulatory network]. BioSystems, 98(3):193-203, 2009M. Mamei, M. Vasirani, F. Zambonelli, [https://www.tandfonline.com/doi/abs/10.1080/08839510490509081 Experiments in morphogenesis in swarms of simple mobile robots]. Applied Artificial Intelligence, 18, 9-10: 903-919, 2004W. Shen, P. Will and A. Galstyan. [http://www.isi.edu/robots/papers/5273188-Shen.pdf Hormone-inspired self-organization and distributed control of robotic swarms]. Autonomous Robots, 17, pp.93-105, 2004H. Hamann, H. Wörn, K. Crailsheim, T. Schmickl: [http://zool33.uni-graz.at/artlife/sites/default/files/hamannIros08.pdf Spatial macroscopic models of a bio-inspired robotic swarm algorithm]. IROS 2008: 1415-1420Y. Jin, H. Guo, and Y. Meng. [http://www.soft-computing.de/SMCB2012Draft.pdf A hierarchical gene regulatory network for adaptive multi-robot pattern formation]. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, 42(3):805-816, 2012H. Guo, Y. Jin, and Y. Meng. [https://www.researchgate.net/profile/Yaochu_Jin/publication/254008061_A_Morphogenetic_Framework_for_Self-Organized_Multirobot_Pattern_Formation_and_Boundary_Coverage/links/559fa2d508ae0e0bf6122f1e/A-Morphogenetic-Framework-for-Self-Organized-Multirobot-Pattern-Formation-and-Boundary-Coverage.pdf A morphogenetic framework for self-organized multi-robot pattern formation and boundary coverage]. ACM Transactions on Autonomous and Adaptive Systems, 7(1), Article No. 15, April 2012. doi:10.1145/2168260.2168275
- "Morphogenetic modular robots" are when modular robots adapt their configuration autonomously using morphogenetic principles;T. Schmickl, J. Stradner, H. Hamann, and K. Crailsheim. [http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.156.6171&rep=rep1&type=pdf 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. 65-72Y. Meng, Y. Zheng and Y. Jin. [https://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5692195 Autonomous self-reconfiguration of modular robots by evolving a hierarchical mechnochemical model]. IEEE Computational Intelligence Magazine, 6(1):43-54, 2011
- "Developmental approaches" deals with the design of the body plan of robots, such as sensors and actuators, as well as the design of the controller, e.g., a neural controller using a generative coding G.S. Hornby and J.B. Pollack. [https://web.archive.org/web/20120310182144/http://idesign.ucsc.edu/papers/hornby_gecco01.pdf Body-brain co-evolution using L-systems as a generative encoding].
Artificial Life, 8:3, 2002 gene regulatory network model.J.A. Lee and J. Sitte. [http://eprints.qut.edu.au/1806/ 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, AustraliaG. Gomez and P. Eggenberger. [https://www.cs.york.ac.uk/rts/docs/CEC-2007/html/pdf/1098.pdf Evolutionary synthesis of grasping through self-exploratory movements of a robotic hand]. Congress on Evolutionary Computation, 2007L. Schramm, Y. Jin, B. Sendhoff. [http://epubs.surrey.ac.uk/532806/1/lschrammECAL09Final.pdf Emerged coupling of motor control and morphological development in evolution of multi-cellular animats]. 10th European Conference on Artificial Life, Budapest, September 2009Y. Meng, Y. Jin and J. Yin. [http://www.soft-computing.de/Submitted20110926.pdf Modeling activity-dependent plasticity in BCM spiking neural networks with application to human behavior recognition]. IEEE Transactions on Neural Networks, 22(12):1952-1966, 2011J. Yin, Y. Meng and Y. Jin. [https://www.researchgate.net/profile/Yaochu_Jin/publication/260662653_A_Developmental_Approach_to_Structural_Self-Organization_in_Reservoir_Computing/links/53f122ff0cf23733e813a228/A-Developmental-Approach-to-Structural-Self-Organization-in-Reservoir-Computing.pdf A developmental approach to structural self-organization in reservoir computing]. IEEE Transactions on Autonomous Mental Development, 2012
See also
References
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External links
- [http://www.soft-computing.de/mr.html A website on Morphogenetic Robotics maintained by Prof. Yaochu Jin]
- [http://www.swarm-organ.eu/ EC FP7 Project: SWARM-ORGAN]
- [https://web.archive.org/web/20100118164705/http://www.symbrion.eu/tiki-index.php European Projects: Symbiotic Evolutionary Robot Organisms (SYMBRION)and Robotic Evolutionary Self-Programming and Self-Assembling Organisms (REPLICATOR)]
- [https://web.archive.org/web/20181110022935/https://lis.epfl.ch/index.html?content=member.php&SCIPER=111729 Laboratory of Intelligent Systems of Prof. Dario Floriano]
- [http://ccsl.mae.cornell.edu/ Cornell Computational Synthesis Laboratory of Prof. Hod Lipson]
- [http://www.demo.cs.brandeis.edu/ Dynamic and Evolutionary Machine Organization Lab of Prof. John Pollack]