The field of autonomous walking robots has been dominated by the trajectory-control approach, which rigidly dictates joint angle trajectories at the expense of both energy efficiency and stability, and the passive dynamics approach, which uses no actuators, relying instead on natural mechanical dynamics as the sole source of control. Although the passive dynamics approach is energy efficient, it lacks the ability to modify gait or adapt to disturbances. Recently, minimally actuated walkers, or dynamic walkers, have been developed that use hip or ankle actuators---knees are always passive---to regulate mechanical energy variations through the timely application of joint torque pulses. Despite the improvement minimal actuation has provided, energy efficiency remains below target values and perturbation rejection capability (i.e., stability) remains poor. In this dissertation, we develop and analyze a simplified robotic system to assess biologically inspired methods of improving energy efficiency and stability in dynamic walkers. Our system consists of a planar, dynamically swinging leg with hip and knee actuation. Neurally inspired, nonlinear oscillators provide closed-loop control without overriding the leg's natural dynamics. We first model the passive stiffness of muscles by applying stiffness components to the joints of a hip-actuated swinging leg. We then assess the effect active knee control has on unperturbed and perturbed leg swinging. Our results indicate that passive joint stiffness improves energy efficiency by reducing the actuator work required to counter gravitational torque and by promoting kinetic energy transfer between the shank and thigh. We also found that active knee control 1) is detrimental to unperturbed leg swinging because it negatively affects energy efficiency while producing minimal performance improvement and 2) is beneficial during perturbed swinging because the perturbation rejection improvement outweighs the reduction in energy efficiency. By analyzing the effects of applying passive joint stiffness and active knee control to dynamic walkers, this work helps to bridge the gap between the performance capability of trajectory-control robots and the energy-efficiency of passive dynamic robots.

Linear springs with variable stiffnesses find some key roles in robotic applications. They are implemented into robotic devices for two main reasons, to increase energy efficiency of walking-running robots and prosthesis, and to get safe human-robot interaction at industrial robots. Being inspired from the human actuation system, a mathematical method to get mechanically adjustable linear springs is noted in the literature / antagonistically working two quadratic springs method. But the proposed solution requires two non-linear springs with quadratic spring characteristics and they are not readily available. Several solutions have been noted in the literature for the acquisition of such non-linear springs. At this thesis work, the solution is realized with a string wrapping around cam mechanism. Two different prototypes were designed and constructed and the second one was physically tested to validate the linear spring behavior. The results displayed good linear spring characteristics with different levels of adjustable spring stiffness. Beside the antagonistically working two quadratic springs method, three novel methods to get mechanically adjustable linear springs are introduced at this thesis. They are based on using hanging weights, an exponential characteristic spring and a linear translation spring respectively. The real prototypes were not manufactured but sample designs using string wrapping around cam mechanisms are made.