Organiser: Dr David Millard
Time: 05/12/2005 12:50-13:40
This talk presents a series of simulated control tasks, that are based on two biologically inspired techniques, to control a two degree of freedom arm, equipped with six compliant actuators.
The first technique, inspired by a biological motor theory called convergent force field control, seeks to use a multi-layer-perceptron (MLP) to steer a custom built dynamic simulation of the arm towards predefined targets within the workspace. The MLP is trained iteratively using mutation hill climbing. The work demonstrates that this approach is capable of creating arm responses that move towards a fixed target from any location within the workspace. That said, the learning approach is not reliable and often gets stuck in local minima. The section concludes by demonstrating the blending of two controllers, to create a smooth range of intermediate results.
The second technique combines convergent force field control with another related biological control theory, called equilibrium trajectory control. Key to the success of this technique is the assumption that smooth natural movements of the tip of the arm can be generated by constant rate movement of the arm's equilibrium point, with respect to the workspace. The model proposed uses a form of convergent force field control to guide an internal representation of the equilibrium point towards a target at a constant rate.
Various implementation options are considered with particular attention paid to the way the equilibrium point is encoded internally. Initial development of the trajectory generator and length encoder indicate that, for reasonable sizes of MLP, shoulder centred polar encoding is the most computationally efficient scheme.
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