Towards a theoretical foundation for morphological computation with compliant bodies
By Helmut Hauser, Auke Jan Ijspeert, R. Füchslin, Rolf Pfeifer, Wolfgang Maass. Biological cybernetics, 2011
365 citations recorded by the source corpus.
The control of compliant robots is, due to their often nonlinear and complex dynamics, inherently difficult. The vision of morphological computation proposes to view these aspects not only as problems, but rather also as parts of the solution. Non-rigid body parts are not seen anymore as imperfect realizations of rigid body parts, but rather as potential computational resources. The applicability of this vision has already been demonstrated for a variety of complex robot control problems. Nevertheless, a theoretical basis for understanding the capabilities and limitations of morphological computation has been missing so far. We present a model for morphological computation with compliant bodies, where a precise mathematical characterization of the potential computational contribution of a complex physical body is feasible. The theory suggests that complexity and nonlinearity, typically unwanted properties of robots, are desired features in order to provide computational power. We demonstrate that simple generic models of physical bodies, based on mass-spring systems, can be used to implement complex nonlinear operators. By adding a simple readout (which is static and linear) to the morphology such devices are able to emulate complex mappings of input to output streams in continuous time. Hence, by outsourcing parts of the computation to the physical body, the difficult problem of learning to control a complex body, could be reduced to a simple and perspicuous learning task, which can not get stuck in local minima of an error function.
Subfields: Biomedical Engineering, Control and Systems Engineering, Mechanical Engineering
View Paper: https://www.semanticscholar.org/paper/b7163f036df1f4833a94670f2356e2ee08991ab9
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Citations in the corpus
- Recent Advances in Physical Reservoir Computing: A Review (2018, background): “A mass–spring network reservoir where mass points are randomly connected to neighboring mass points via nonlinear springs was proposed in Hauser, Ijspeert, Füchslin, and Maass (2011).”
- Physical reservoir computing—an introductory perspective (2020, background): “Helmut Hauser et al. tried to propose a framework to theoretically investigate the morphological computation of compliant bodies [109].”
- MakeSense: Automated Sensor Design for Proprioceptive Soft Robots (2019, background): “By exploiting morphological computation 28 , simpler control strategies are sufficient to reliably grasp and manipulate deformable objects of varying shape, size, and stiffness, or to locomote in unpredictable terrains, trapped with obstacles.”
- Information Processing Capacity of Dynamical Systems (2012, background): “Recent insight in robotics has demonstrated that the control of animal and robot locomotion can greatly be simplified by exploiting the physical body’s response to its environment 10,11 .”