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Towards a theoretical foundation for morphological computation with compliant bodies
Helmut Hauser1, Auke J Ijspeert, Rudolf M Füchslin
1Artificial Intelligence Laboratory, Department of Informatics, University of Zurich, Andreasstrasse 15, 8050 Zurich, Switzerland. hhauser@ifi.uzh.ch
Biological Cybernetics
|February 1, 2012
Summary
This study introduces a mathematical model for morphological computation in compliant robots. It shows that robot body complexity and nonlinearity can be harnessed for computation, simplifying robot control learning.
Area of Science:
- Robotics
- Control Theory
- Computational Mechanics
Background:
- Controlling compliant robots is challenging due to complex, nonlinear dynamics.
- Morphological computation views physical non-rigidity as a computational resource, not a defect.
Purpose of the Study:
- To develop a theoretical framework for understanding morphological computation in compliant bodies.
- To mathematically characterize the computational contribution of a robot's physical structure.
Main Methods:
- Developed a mathematical model for morphological computation with compliant bodies.
- Utilized simple mass-spring systems to model physical bodies.
- Integrated a static, linear readout mechanism.
Main Results:
- Demonstrated that physical body complexity and nonlinearity are beneficial for computation.
- Showed that mass-spring systems can implement complex nonlinear operators.
- Enabled emulation of complex input-output mappings in continuous time.
Conclusions:
- Outsourcing computation to the physical body simplifies robot control learning.
- The proposed approach reduces complex learning tasks to simpler ones, avoiding local minima.
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