Research On Perfor Mance And A Power Input Method Of A Passive Dynamic Walker

The first passive dynamic walker is a pure passive walker which can perform a stable walking motion down a slight slope powered only by gravity. Powered robots that can walk on a level floor by ankle push-off or hip actuation have also been built based on this concept. Compared with traditional walking robots, passive dynamic walkers have more natural-looking gait and higher energy efficiency. The research results can be used to the design of biped robots, medical rehabilitation devices and prosthetic legs to help rehabilitation for the amputees. The performance of a passive dynamic walker and a power input method for a quasi-passive dynamic walker is studied in this paper.A 2D kneeless biped passive walking prototype with hip spring and offset of center of mass was proposed. The equations of motion of the swing phase and the impact phase were derived, respectively. The equations were solved with MATLAB software by numerical simulation. The stable fixed point was obtained by Newton-Raphson iteration. The numerical simulation is verified by virtual prototype simulation and experiment, respectively.The effects of spring stiffness, damping coefficient and offset of center of mass on disturbance rejection, walking speed, walking efficiency and bifurcation characteristics were studied. Reciprocal of the gait sensitivity norm was used as a measure for disturbance rejection. The dimensionless mechanical cost of transport was used as a measure for walking efficiency. The effects of spring stiffness and offset of center of mass on disturbance rejection are verified by experiments. For experiments, we quantified disturbance rejection by observing 100 passive walking trials down a gentle slope of finite length and recording the fraction of trials which successfully walked to the end. The experiments show that an optimal spring stiffness and an optimal backward offset of center of mass for disturbance rejection exist. The method of adjusting spring stiffness and offset of center of mass has the advantages of easy to implement and improving disturbance rejection significantly. The reasons of the effects of spring stiffness, damping coefficient and offset of center of mass on disturbance rejection were investigated.To improve disturbance rejection is a research focus of passive dynamic walker. Multi-parameter optimization is a very effective way to improve disturbance rejection. The genetic algorithm combined with pattern search method was used to find the maximum reciprocal of the gait sensitivity norm. Four optimal parameters were spring stiffness, offset of center of mass, axial displacement of center of mass and moment of inertia. Obtaining the stable fixed point is the premise of obtaining the gait sensitivity norm. Newton-Raphson method does not converge with improper initial values. The search time and successful search rate are dependent on the initial value. BP neural network was used to estimate the fixed point, and the estimated fixed point was taken as initial value for Newton-Raphson iteration to search the stable fixed point. Small variation of parameters leads to small variation of fixed points. When calculating fixed points of two successive samples, only one parameter had a small variation. The fixed point obtained with Newton-Raphson iteration was used as initial value for the next sample. 1000 groups of parameters were generated randomly to test the performance of the neural network. The results show that this method increases the successful search rate significantly and reduces the search time significantly. This method was used to obtain the stable fixed points for the optimization. The genetic algorithm was used for global optimization, then the optimal parameter was used as initial value for pattern search method to optimize locally. The effectiveness of the optimization is verified by comparing the optimal result with the prototype's reciprocal of the gait sensitivity norm.The present control methods for quasi-passive walkers are complex. Inspired by biomechanics in human walking, we presented a power input method for the quasi-passive walker and quantitatively studied the effects of parameters on the performance of the quasi-passive walker. After the impact between swing leg and ground, a square wave torque was applied at the hip as power input. Since the torque does not do negative work during the whole walking period, the walker has a high walking efficiency as human walking. The robot can walk up a slope, walk down a slope and walk on flat ground. The falling gait and bifurcation gait can be controlled to stable period-1 gait by properly adjusting power input parameters. The quasi-passive walker can walk with stable period-1 gait in a larger scope of slope angle compared with the pure passive walker.