Actually the photo is from the Biologically Inspired Robots Group at EPFL in Switzerland.
Photograph by A.Herzog, courtesy Biologically Inspired Robotics Group, EPFL
This group of roboticists is interested in modeling animal locomotion both to gain insight into how to design systems to coordinate robotic movement and to understand the evolution of animal locomotion. The scientists began with a model of lamprey locomotion, lampreys being relatively simple aquatic vertebrates, and built a lamprey robot to test their understanding of this organism's coordination.
They then were able to show how the same basic control systems are able to coordinate movement of a terrestrial animal, that is a salamander, with very minor changes in the characteristics of the control system.
Lamprey photo courtesy of the Fish and Wild Life Service.
Non scientists often accuse scientists of being reductionistic. But such criticism misses a key aspect of science, and that is once scientists think they understand how something works in terms of its parts, scientists routinely attempt to test their understanding by putting the parts together to see how the resulting construct compares with the original whole.
This applies to understanding salamander locomotion in order to answer basic questions about evolution and robotics as well as deep problems such do we understand enough about how cells work to make an artificial cell that mimics the features of natural cells. This problem is still out of reach but as this article shows we are making progress. It is this synthetic (dare I use holistic) aspect of science that gives science its explanatory power whether we are talking cells, salamanders or evolution.
A.J. Ijspeert, A. Crespi, D. Ryczko, and J.M. Cabelguen. From swimming to walking with a salamander robot driven by a spinal cord model. Science, 9 March 2007, Vol. 315. no. 5817, pp. 1416 - 1420, 2007.
A.J. Ijspeert, A. Crespi, and J.M. Cabelguen. Simulation and robotics studies of salamander locomotion. Applying neurobiological principles to the control of locomotion in robots. Neuroinformatics, 3(3):171-196, 2005.
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