Optimal trajectory generation method to find a smooth robot joint trajectory based on multiquadric radial basis functions

A new technique to generate smooth motion trajectories for robot manipulators using multiquadric radial basis functions (MQ-RBFs) is presented in this paper. In order to get the optimal trajectory, two objective functions are minimized that are proportional to the execution time, the integral of the squared jerk (which denotes the time derivative of the acceleration) along the whole trajectory. Also, the proposed interpolation technique is introduced for solving the trajectory planning problem in the joint space, where the interpolation of via-points takes into account boundary conditions and also satisfies kinematics limits of velocity, acceleration, and jerk. Then, the proposed approach is compared with a set of classical interpolation techniques based on radial basis function models and cubic splines. Finally, the proposed technique has been tested for the six-joint PUMA 560 manipulator in two cases (minimum time and minimum time-jerk) and results are compared with those proposed of other important trajectory planning techniques. Numerical results show the competent performances of the proposed methodology to generate trajectories in short total transfer time and with high smooth profile.

Automated summary

This paper presents a new technique using multiquadric radial basis functions to generate smooth motion trajectories for robot manipulators. By minimizing two objective functions, an optimal trajectory is obtained which takes into account the execution time and the jerk along the entire trajectory. With the proposed interpolation technique, the trajectory planning problem in joint space is effectively solved, satisfying kinematics limits. Experimental results demonstrate the competent performances of this technique in generating smooth trajectories in short transfer time.