Accelerometer Based Evaluation of Industrial Robot Kinematics Derived in Maple

Abstract

In this paper a step toward making a toolbox for industrial robot modelling based on the computer algebra tool Maple is taken. It can be seen as a modelling platform for efficient derivation of the necessary equations for doing, eg, sensor fusion or state estimation by an Extended Kalman Filter (EKF) algorithm. Forward kinematics is studied and the position and orientation of the robot tool are determined in terms of the Denavit-Hartenberg joint variables. Linear and angular velocities and accelerations are derived using the Jacobian. The toolbox is exemplified using an IRB1400 from ABB Robotics with a so called parallelogram linkage structure. The kinematic relations received are verified using the robot IRB1400 with an accelerometer placed on the robot tool and it is shown that measured acceleration and theoretical acceleration derived from the kinematics agree well. However no flexibilities in the modelling are taken into account, which results in differences between measured and derived acceleration when several motors of the robot cooperate in the motion.