Abstract:

To achieve stable walking by an intelligent humanoid robot, this thesis proposes a center of gravity (COG) trajectory planner, immediate change footstep controller, ankle stabilizer, and stereo vision assisted footstep planner. After assembling these elements, the humanoid robot walked stably on rugged terrain and explored a road suitable for walking. Finally, to reduce energy and weight, we designed a leg mechanism with a larger weight to mass ratio for use on our strictly weight-limited humanoid robot.

For COG trajectory generation, we used a preview control COG generator for intelligent walking. Due to the difficulties after a sudden change of footsteps, we proposed an immediate modification of the foot placement controller. Combining the advantages of the two controllers, we planned the footsteps and COG trajectory dynamically and the robot walked more freely. The ankle stabilizer was implemented to reinforce walking stability. Utilizing the controllers, our robot walked stably on the most rugged terrain. Finally, stereo vision is the window into the core of our humanoid robot. We made our humanoid robot more intelligent by composing stereo vision data and dynamic footstep planning. With this intelligence, the robot could analyze, all by itself, its environment and find the locations of obstacles, accessible regions, and the route to its destination. Finally, in order to reduce the weight and energy consumption of the humanoid robot, we used Finite Element stress analysis to remove any unnecessary materials and, on the other hand, to keep the structure strong enough to maximize the payload.

Finally, our simulation physical environment was constructed on ADAMS, and all of the control code was built in MATLAB. These two environments are connected by Simulink in MATLAB. Stress analysis was done using COSMOSWorks in SolidWorks.