Abstract
M.Ing. (Mechanical Engineering)
The research reported in this thesis describes the design and simulation of a neural controller for a
three -degree-of-freedom robot leg for use as an hexapod leg . Biological systems are considered as a
motivation to develop the neural control system for hexapod walking on a horizontal surface .
Backpropagation training of multilayer perceptrons and a combination of heterogeneous neurons are
used to implement several pattern generators with different behaviours. The artificial neurons are
simulated and connected together with the pattern generators to form a complete control system .
Previous work [48] shows the performance of a two -degree-of-freedom leg controller - this type of
controller however cannot compensate for surface irregularities , The control system for the three degree-of-freedom leg is then further extended to compensate for surface irregularities that cannot be
traversed by the two -degree-of-freedom leg.