Modular Framework Kinematic and Fuzzy Reward Reinforcement Learning Analysis of a Radially Symmetric Six-Legged Robot

Abstract

Hexapod Robots gives us the ability to study walking robots without facing problems such as stability in many aspects. It has a great deal of flexibility in movement even if a leg becomes malfunctioned. Radially symmetric (hexagonal) hexapods have more flexibility in movement than rectangular leg alignments. Because of symmetry they can move in any direction and time efficiently. Inverse kinematic problem of this kind of hexapods is solved through a modular mobile view considering six degrees of freedom for the trunk. Then typical tripod and wave gaits are analyzed and simulated through the presented formulation. In Reinforcement Learning algorithm for walking it is important how to make reward signal with respect to robot's actions and states. A fuzzy approach is presented and analyzed to generate reward signals. It is shown that the presented fuzzy system generates more considerable accurate rewards with better performance than functional rewards which are used in walking learning problems. (Mohammadali Shahriari*, Kambiz Ghaemi Osguie, Amir Ali Akbar Khayyat Modular Framework Kinematic And Fuzzy Reward Reinforcement Learning Analysis Of A Radially Symmetric Six-Legged Robot. Life Sci J 2013;10(8s):120-129) (ISSN:1097-8135). http://www.lifesciencesite.com. 15