A Metaheuristic Optimization Approach for Trajectory Tracking of Robot Manipulators
Carlos López-Franco, Dario Diaz, Jesús Hernández-Barragán, Nancy Arana‐Daniel, Michel López-Franco
Abstract
Due to the complexity of manipulator robots, the trajectory tracking task is very challenging. Most of the current algorithms depend on the robot structure or its number of degrees of freedom (DOF). Furthermore, the most popular methods use a Jacobian matrix that suffers from singularities. In this work, the authors propose a general method to solve the trajectory tracking of robot manipulators using metaheuristic optimization methods. The proposed method can be used to find the best joint configuration to minimize the end-effector position and orientation in 3D, for robots with any number of DOF.
Topics & Concepts
TrajectoryJacobian matrix and determinantRobotMetaheuristicComputer scienceControl theory (sociology)Robot end effectorKinematicsPosition (finance)Tracking (education)Gravitational singularityTrajectory optimizationArtificial intelligenceMathematical optimizationMathematicsOptimal controlControl (management)Classical mechanicsPhysicsMathematical analysisEconomicsFinanceAstronomyPedagogyApplied mathematicsPsychologyRobotic Mechanisms and DynamicsRobotic Path Planning AlgorithmsPiezoelectric Actuators and Control