This paper presents a framework to generate dynamic walking for biped robots. A set of self-stable gait primitives is first constructed. It is done by 1) representing parametric gait primitives, 2) utilizing state-dependent torque control, and 3) doing numerical optimization that takes into account the complex multi-body dynamics with frictional contact forces. Dynamic walking to follow the arbitrary path including a curve is then generated online via sequentially composing primitive motions. Results show that dynamic gaits are humanlike and efficient compared to the conventional knee bent walkers. Our proposed method is applied to a torque-controlled, human-sized biped robot platform, 'Roboray' which is cable-driven partially for joint compliance. Following a discussion on robot design and control, experimental results are also reported.