VODE: a variable-coefficient ODE solver
SIAM Journal on Scientific and Statistical Computing
Learning internal representations by error propagation
Parallel distributed processing: explorations in the microstructure of cognition, vol. 1
Intelligence without representation
Artificial Intelligence
Being There: Putting Brain, Body, and World Together Again
Being There: Putting Brain, Body, and World Together Again
Embodied cognition: a field guide
Artificial Intelligence
How the Body Shapes the Way We Think: A New View of Intelligence (Bradford Books)
How the Body Shapes the Way We Think: A New View of Intelligence (Bradford Books)
Stable Output Feedback in Reservoir Computing Using Ridge Regression
ICANN '08 Proceedings of the 18th international conference on Artificial Neural Networks, Part I
Robotics and Autonomous Systems
Towards a theoretical foundation for morphological computation with compliant bodies
Biological Cybernetics
Parallel Reservoir Computing Using Optical Amplifiers
IEEE Transactions on Neural Networks
Hi-index | 0.00 |
Embodiment has led to a revolution in robotics by not thinking of the robot body and its controller as two separate units, but taking into account the interaction of the body with its environment. By investigating the effect of the body on the overall control computation, it has been suggested that the body is effectively performing computations, leading to the term morphological computation. Recent work has linked this to the field of reservoir computing, allowing one to endow morphologies with a theory of universal computation. In this work, we study a family of highly dynamic body structures, called tensegrity structures, controlled by one of the simplest kinds of "brains." These structures can be used to model biomechanical systems at different scales. By analyzing this extreme instantiation of compliant structures, we demonstrate the existence of a spectrum of choices of how to implement control in the body-brain composite. We show that tensegrity structures can maintain complex gaits with linear feedback control and that external feedback can intrinsically be integrated in the control loop. The various linear learning rules we consider differ in biological plausibility, and no specific assumptions are made on how to implement the feedback in a physical system.