Rolling direction prediction of tensegrity robot on the slope based on FEM and GA

Abstract

Six-strut tensegrity robot is a new mobile robot whose outer surface is an icosahedron containing 8 regular triangles and 12 isosceles triangles, and the robot performs rolling locomotion along the edges of the triangle. On the slope, it has lots of poses depending on the slope’s angles and positions of robot, which is difficult to control the rolling directions in the real world. This paper proposed a new method based on finite element method and a genetic algorithm to predict the rolling directions of the robot. The balanced forces equations of robot nodes are established using finite element method, which is a constrained optimization problem. The equations are transformed into an unconstrained optimization problem by the thinking of sequential unconstrained minimization technique. Finally, the unconstrained optimization problem is calculated by genetic algorithm, and the relations between the actuators and the rolling directions are obtained through the dot product of gravitational torque and the edge vector of bottom triangle. This method is verified by simulation and experiment results.