Evolutionary approaches for legged robot control
Evolutionary approaches for legged robot control
Due to their morphologies, legged robots are ideal platforms for investigating biologically-inspired approaches to control and navigation.
We are currently investigating the application of evolutionary/machine learning techniques to generate task-specific and platform-specific controllers, targeting improved performance.
As an example, depending on the control system, variation of joint controller gain values provide a way to decrease energy consumption during operation.
We present a fully automated hardware optimisation test-bed that use Evolutionary Algorithms to find a optimal set of controller parameters that increase locomotion performance.
![](https://i0.wp.com/research.csiro.au/robotics/wp-content/uploads/sites/96/2017/02/2016-06-16-12.51.30.jpg?resize=640%2C349&ssl=1)
Baldwin on testbed
A testbed that evolves hexapod controllers in hardware
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