This paper describes a new method for generating
the turning-gait of a six-legged robot using a combined
genetic algorithm (GA)-Fuzzy approach. The main drawback
of the traditional methods of gait generation is their
high computational load. Thus, there is still a need for
the development of a computationally tractable algorithm
that can be implemented online to generate stable gait
of a multilegged robot. In the proposed genetic-fuzzy
system, the fuzzy logic controllers (FLCs) are used to
generate the stable gait of a hexapod and a GA is used
to improve the performance of the FLCs. The effectiveness
of the proposed algorithm is tested on a number of turning-gait
generation problems of a hexapod that involve translation
as well as rotation of the vehicle. The hexapod will have
to take a sharp circular turn (either clockwise or counter-clockwise)
with minimum number of ground legs having the maximum average
kinematic margin. Moreover, the stability margin should
lie within a certain range to ensure static stability of
the vehicle. Each leg of a six-legged robot is controlled
by a separate FLC and the performance of the controllers
is improved by using a GA. It is to be noted that the actual
optimization is done off-line and the hexapod can use these
optimized FLCs to navigate in real-world scenarios. As
an FLC is computationally less expensive, the proposed
algorithm will be faster compared with the traditional
methods of gait-generation, which include both graphical
as well as analytical methods. The GA-tuned FLCs are found
to perform better than the author-defined FLCs.
2A2-V03 Extended Normalized Energy Stability Margin(Walking Robot (2))