Inverse kinematics of Manipulator Robot using a PSO Metaheuristic with Adaptively Exploration

Abstract

The solution of the inverse kinematics in robotics is very important, and it becomes more difficult in robotic manipulators with many degrees of freedom. There are several methods of solution such as algebraic, kinematic decoupling, numerical and recently metaheuristics. This paper proposes the particle swarm metaheuristics characterized by having inertia weight and acceleration coefficients of the particles that vary exponentially in each iteration of the algorithm allowing an adaptively exploration, besides the objective function to minimize considers both the position and orientation error using direct kinematics. The proposed PSO algorithm avoid to fall into wrong joint angles configurations and have better performance in comparison to the conventional algorithm improving its repeatability.