dynamically stable biped robots mimicking human locomotion have received significant attention over the last few decades. formerly, the existence of stable periodic gaits for straight walking of passive biped walkers was well known and investigated as the notion of passive dynamic walking. this study is aimed to elaborate this notion in the case of three dimensional (3d) walking and extend it f...

Biped robots’ locomotion is realized by driving the joint motion via a drive chain. Therefore, stiffness of chain an important factor that affects performance and can influence behavior biped robot. This work focused on leg’s using mass-spring model based robot AIRO built in Zhejiang Lab. Methods for determination parameters proposed were presented, including use ANSYS Workbench to determine in...

al. [3] in the case of a humanoid robot based on hybrid fuzzy control methods. This paper proposes a bipedal locomotion controller using an optimized Neuro-Fuzzy inference structure. In which, it is based on an adaptive neuro-fuzzy inference identifier (ANFII) for modeling the inverse dynamics of the biped robot. The proposed learning scheme is based on the zero moment point (ZMP); while the mo...

This paper presents the results of experiments in applying a spiking neural network to control the locomotion of a simulated biped robot. The neural model used in simulations was developed to allow for an analytic solution to a neuron’s fire time, while maintaining a non-instant post-synaptic potential rise time. The synaptic weights and delays were tuned using an evolution-strategy. Simulation...

In this paper we discuss the passivity based control of the two-link robot known as the Compass Gait Biped. Starting from a narrow region of initial conditions, the compass gait biped is capable of locomotion down shallow inclines without actuation or feedback control of any kind. We will discuss some feedback control strategies that can exploit these passive dynamics by shaping the energy of t...

We describe an evolutionary approach to the control problem of bipedal walking. Using a full rigid-body simulation of a biped, it was possible to evolve recurrent neural networks that controlled stable straight-line walking on a planar surface. No proprioceptive information was necessary to achieve this task. Furthermore, simple sensory input to locate a sound source was integrated to achieve d...