Hexapod Robot Static Stability Enhancement using Genetic Algorithm


Hexapod robot is a flexible mechanical robot with six legs. It has the ability to walk over terrain. The hexapod robot look likes the insect so it has the same gaits. These gaits are tripod, wave and ripple gaits. Hexapod robot needs to stay statically stable at all the times during each gait in order not to fall with three or more legs continuously contacts with the ground. The safety static stability walking is called (the stability margin). In this paper, the forward and inverse kinematics are derived for each hexapod’s leg in order to simulate the hexapod robot model walking using MATLAB R2010a for all gaits and the geometry in order to derive the equations of the sub-constraint workspaces for each hexapod’s leg. They are defined as the sub-constraint workspaces volumes when the legs are moving without collision with each other and they are useful to keep the legs stable from falling during each gait. A smooth gait was analyzed and enhanced for each hexapod’s leg in two phases, stance phase and swing phase. The proposed work focused on the two approaches first, the modified classical stability margins. In this approach, the range of stability margins is evaluated for all gaits. The second method is called stability margins using Genetic Algorithm (GA) that enhanced the static stability by getting the best stability margins for hexapod robot and these results are useful to get best stable path planning of hexapod robot with smaller error than the first approach and with better new stable coordinates of legs tips than the first method. In addition, the second approach is useful for getting the better new stable center body coordinates than center body coordinates in the first approach of hexapod robot.