A novel algorithm combined with single mapping workspace and Genetic Algorithm for solving inverse kinematic problem of redundant manipulators
The number of a redundant manipulator’s DOF is greater than the number of the workspace’s dimensions, creating difficulty in solving its inverse kinematics. In the workspace, each pose corresponds to infinite number of an-gles of the arm. As a result this means that the traditional inverse kinematics so-lution method is computationally large and complex. With the aim of trajectory planning, an inverse kinematics algorithm based on the genetic algorithm has been proposed in this paper to generate a smooth trajectory. The initial pose of the arm was taken as the initial condition, then the constraint function, a reduction in the search interval and a smooth reward function was used, and finally the genetic algorithm was implemented. It was found that this method greatly reduced the solution of the large angular momentum of the arm and tended to choose a smoother solution. Through the use of the constraint function and the smooth reward function as the optimization index, the inverse kinematic solution corresponding to the preset trajectory was able to be effectively solved.
KeywordsRedundant manipulator Constraint function Smooth reward function Genetic algorithm
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