Abstract:
Development of full size humanoid robots can be simplified along with the bipedal
walking formulation methods. These robots consist of rigid bodies connected with
actuated joints supposed to mimic human like walking. Although many researchers have
tackled the problem of bipedal dynamic walking, it is far from matching human skills.
This particular problem is of the special interest and the main subject of this research.
Biped robot walking is a periodic path of an unstable phase, called Single Support
Phase, following a stable phase, Double Support Phase. A periodic approach providing a
scalable gait with characteristic parameters such as gait length, gait maximum height and
gait time cycle is proposed. The methodology is divided in two parts, planning robot
trajectory and dynamic stability examination. The lower body is responsible for the
general bipedal walking trajectory where limited numbers of breakpoints in both stable
and unstable phase are identified. Consequently, positions of ankle, hip, and knee joints
are derived for a seven link biped robot. In order to generate a smooth walking trajectory,
a search for fast and efficient computation algorithms resulted in exploring the field of
Artificial Intelligence and Soft Computing with the purpose of finding a valid nonconventional
approach. The represented approach for walking pattern planning based on
Artificial Neural Networks using Radial Basis Function is intended to fit a curve on
derived breakpoints.
Biped robot stability during walking cycles is investigated using the Zero Moment
Point criterion. In the dynamic stability study part, ZMP for a stable condition in a
determined polygon of support is calculated in every single gait step. Then, for trunk
motion adjustment in order to compensate for lower limb movement, Linear Inverted Pendulum model and ZMP criterion are employed to obtain upper body trajectory
satisfying whole robot walking dynamic stability.
Keywords: Artificial Neural Networks, Radial Basis Functions, Bipedal Robot
Walking, Trajectory Planning, Zero Moment Point, Dynamic Stability
Description:
A Thesis Submitted to the Faculty of Graduate Studies and Research In Partial Fulfillment of the Requirements for the Degree of Master of Applied Science in Industrial Systems Engineering, University of Regina. xiii, 124 p.