Bilateral Decoupling in the Neural Control of Biped Locomotion

In this paper, a bilaterally decoupled neural controller was used to achieve stable locomotion in a 6 DOF biped robot with 5 links, implemented in a virtual physics-based simulation environment. The neural controller consists of an independent neural rhythm generator for each leg. The rhythm generator is a recurrent neural network, whose weights are optimized by a genetic algorithm and are identical for both legs. Each one receives inputs only from its own joint angle sensors and touch sensor on the foot, and produces motor commands for joints of the same leg. However, by using sensory feedback from the mechanical coupling of the legs through the body, they can synchronize to produce coordinated stepping movements. Furthermore, improvements in the quality of the gait can be achieved only with global sensory information. The results suggest the possibility that there may not be a need for explicit contralateral sensory coupling or neural connections in bipedal locomotion.