Incremental Evolution of Three Degree-of-Freedom Arachnid Gaits

In this research, we evolve gaits for an arachnid-inspired robot. The method used is an expansion upon previous research on the incremental evolution of gaits for hexapod robots with two degrees of freedom per leg, which we now apply to a more complex, eight-legged robot with three degrees of freedom per leg. Incremental evolution handles gait generation for legged robots in two discrete increments. The first increment uses a cyclic genetic algorithm to learn the activations (pulse instructions to the servos) required for each leg to perform a single-leg cycle. This learning program takes into account the way each leg is mounted on the body and the range of movement provided by the three servos on each leg to produce a smooth, straight, and efficient leg cycle. The second increment uses a genetic algorithm to select the best combination of leg cycles for each leg and to learn the timing to execute each leg cycle to coordinate them all together into a single gait. In this work, we learn the gait incrementally in a simulation and transfer the final gaits to the real robot to confirm the method's viability.