Abstract
Robots can be used to instantiate and test hypotheses about biological systems. This approach to modelling can be described by a number of dimensions: relevance to biology; the level of representation; generality of the mechanisms; the amount of abstraction; the accuracy of the model; how well it matches the behaviour; and what medium is used to construct the model. This helps to clarify the potential advantages of this methodology for understanding how behaviour emerges from interactions between the animal, its task and the environment.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Bibliography
J. Ayers, P. Zavracky, N. Mcgruer, D. Massa, V. Vorus, R. Mukherjee, and S. Currie. A modular behavioural-based architecture for biomimetic autonomous underwater robots. In Autonomous Vehicles in Mine Countermeasures Symposium, 1998.
R.D. Beer, H.J. Chiel, R.D. Quinn, and R.E. Ritzmann. Biorobotic approaches to the study of motor systems. Current Opinion in Neurobiology, 8(6):777–782, 1998.
M. Blanchard, RF.M.J Verschure, and F. Claire Rind. Using a mobile robot to study locust collision avoidance responses. International Journal of Neural Systems, 9(5):405–410, 1999.
V. Braitenberg. Vehicles: experiments in synthetic psychology. MIT Press, Cambridge, MA, 1984.
R. J. Brooks and A. M. Tobias. Choosing the best model: level of detail, complexity and model performance. Mathematical Computer Modelling, 24(4):1–14, 1996.
B. Cartwright and T. Collett. Landmark learning in bees. Journal of Comparative Physiology A, 151:521–543, 1983.
K.H. Chan and P.M. Tidwell. The reality of artificial life: can computer simulations become realizations? In submission to Third International Conference on Artificial Life, 1993.
A.M. Flynn and R.A. Brooks. Battling reality. Technical Report A.I. Memo 1148 M.I.T. A.I. Lab, M.I.T., 1989.
N. Franceschini, J.M. Pichon, and C. Blanes. From insect vision to robot vision. Philosophical Transactions of the Royal Society B, 337:283–294, 1992.
F. Grasso, T. Consi, D. Mountain, and J. Atema. 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, 2000.
B. Hannaford, J. Winters, C-P Chou, and P-H Marbot. The anthroform biorobotic arm: a system for the study of spinal circuits. Annals of Biomedical Engineering, 23:399–408, 1995.
R. R. Harrison and C. Koch. A robust analog VLSI motion sensor based on the visual system of the fly. Autonomous Robotics, 7(3):211–224, 1999.
O. Holland and C. Melhuish. Stigmergy, self-organization and sorting in collective robotics. Artificial Life, 5:173–202, 1999.
S.A. Huber and H.H. Bulthoff. Simulation and robot implementation of visual orientation behaviour of flies. In R. Pfeifer, B. Blumberg, J.A. Meyer, and S.W. Wilson, editors, From animals to animats 5, pages 77–85, Cambridge, Mass., 1998. MIT Press.
H. Ishida, A. Kobayashi, T. Nakamoto, and T. Moriisumi. Three dimensional odor compass. IEEE Transactions on Robotics and Automation, 15:251–257, 1999.
A. Kaplan. The conduct of enquiry. Chandler, San Francisco, 1964.
Y Kuwana and H Shimoyama, I; Miura. Steering control of a mobile robot using insect antennae. In IEEE International Conference on Intelligent Robots and Systems, volume 2, pages 530–535, 1995.
D. Lambrinos, M. Maris, H. Kobayashi, T. Labhart, R. Pfeifer, and R. Wehner. An autonomous agent navigating with a polarized light compass. Adaptive Behaviour, 6(l):175–206, 1997.
D. Lambrinos, R. Möller, T. Labhart, R. Pfeifer, and R. Wehner. A mobile robot employing insect strategies for navigation. Robotics and Autonomous Systems, 30(1–2):39–64, 2000.
R. Möller, D. Lambrinos, R. Pfeifer, T. Labhart, and R. Wehner. Modeling ant navigation with an autonomous agent. In R. Pfeifer, B. Blumberg, J.A. Meyer, and S.W. Wilson, editors, From animals to animats 5, Cambridge, Mass., 1998. MIT Press.
T.M. Morse, T.C. Ferree, and S.R. Lockery. Robust spatial navigation in a robot inspired by chemotaxis in Caenorrhabditis elegans. Adaptive Behaviour, 6(3/4):393–410, 1998.
D.W. Onstad. Population-dynamics theory-the roles of analytical, simulation, and supercomputer models. Ecological Modelling, 43(1–2):111–124, 1988.
N. Oreskes, K. Shrader-Frechette, and K. Belitz. Verification, validation and confirmation of numerical models in the earth sciences. Science, 263:641–646, 1994.
J-M Pichon, C. Blanes, and N. Franceschini. Visual guidance of a mobile robot equipped with a network of self-motion sensors. In W.J. Wolfe and W.H. Chun, editors, Mobile Robots IV, volume 1195, pages 44–53, Bellingham, 1989. Society of Photo-optical Instrumentation Engineers.
R.D. Quinn and K.S. Espenscheid. Control of a hexapod robot using a biologically inspired neural network. In R.D. Beer, R.E. Ritzmann, and T. McKenna, editors, Biological Neural Networks in Invertebrate Neuroethology and Robotics. Academic Press, London, 1993.
R.D. Quinn and R.E. Ritzmann. Construction of a hexapod robot with cockroach kinematics benefits both robotics and biology. Connection Science, 10:239–254, 1998.
A. Rosenblueth and N. Wiener. The role of models in science. Philosophy of Science, 12(4):316–321, 1945.
M Rucci and J Edelman, GM; Wray. Adaptation of orienting behavior: from the barn owl to a robotic system. IEEE Transactions on Robotics and Automation, 15(1):p 96–110, February 1999.
F. Saito and T. Fukuda. A first result of the brachiator III-A new brachiation robot modeled on a siamang. In C. Langton and K. Shimohara, editors, Proceedings of ALife V, Cambridge MA, 1996. MIT Press.
L.M. Saksida, S.M. Raymond, and D.S. Touretzky. Shaping robot behavior using principles from instrumental conditioning. Robotics and Autonomous Systems, 22(3–4):231–249, 1997.
E.L. Schwartz. Introduction. In E.L. Schwartz, editor, Computational Neuroscience. MIT Press, Cambridge, Mass., 1990.
T. Shibata and S. Schaal. Robot gaze stabilisation based on mimesis of oculomotor dynamics and vestibulocerebellar learning. Advanced Robotics, 13(3):351–352, 1999.
M.V. Srinivasan and S. Venkatesh. From, Living Eyes to Seeing Machines. Oxford University Press, Oxford, 1997.
M.V. Srinivasan, J.S. Chahl, K. Weber, and S. Venkatesh. Robot navigation inspired by principles of insect vision. Robotics and Autonomous Systems, 26:203–216, 1999.
M.S. Triantafyllou and G.S. Triantafyllou. An efficient swimming machine. Scientific American, 272(March):40–48, 1995.
B. Webb. Can robots make good models of biological behaviour? Be havioural and Brain Sciences, 24(6): 1033–1094, 2001.
B. Webb and T. Scutt. A simple latency dependent spiking neuron model of cricket phonotaxis. Biological Cybernetics, 82(3):247–269, 2000.
J. Weiner. On the practice of ecology. Journal of Ecology, 83(1):153–158, 1995.
B. P. Zeigler. Theory of Modelling and Simulation. John Wiley, New York, 1976.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2008 CISM, Udine
About this chapter
Cite this chapter
Webb, B. (2008). Using robots to model biological behaviour. In: Arena, P. (eds) Dynamical Systems, Wave-Based Computation and Neuro-Inspired Robots. CISM International Centre for Mechanical Sciences, vol 500. Springer, Vienna. https://doi.org/10.1007/978-3-211-78775-5_8
Download citation
DOI: https://doi.org/10.1007/978-3-211-78775-5_8
Publisher Name: Springer, Vienna
Print ISBN: 978-3-211-78774-8
Online ISBN: 978-3-211-78775-5
eBook Packages: EngineeringEngineering (R0)