Abstract:

This thesis examines the walking motion of human beings and applies its findings to a humanoid robot developed by our laboratory. Our goal is to construct the usable Zero Moment Point (ZMP) trajectory, a Center of Gravity (COG) trajectory in the vertical direction, and momentum compensation. Conventional ZMP trajectories applied to humanoid robots are usually located at the center of each foot pad, shifting instantaneously to the new supporting leg as support changes from one foot to another. Velocity and acceleration become unsmooth. We used Preview Control to generate a COG trajectory with the ability to arbitrarily adjust position in the vertical direction. Observations of human walking motion enabled us to plan COG trajectory with continuous smooth change of velocity and acceleration. The robot now has no need to keep its knee joints constantly bent, and therefore consumes less power. Its natural walk is a result of integrating the adjusting ZMP and COG trajectory controls by using the modified inverse kinematics algorithm. This thesis proposes two methods to derive the toe-off and heel-contact motions necessary for a natural walk. The proposed algorithms are justified through simulation and experiments. Our simulation physical environment was constructed on MSC ADAMS, and all controlling functions were built in MathWorks MATLAB. The two software environments were connected by Simulink in MATLAB. We also developed a humanoid robot with new foot pads to generate a natural walk. All mechanisms were designed in Dassault Systems SolidWorks, and stress analysis performed using Dassult Systems CATIA.