In this paper an analysis of the experimental results yielded by a minimum time-jerk trajectory planning algorithm is presented. The technique considers both the execution time and the integral of the squared jerk along the trajectory, and the kinematic constraints of the robot manipulator under test. The need for a fast execution and the need for a smooth trajectory are taken into account by adjusting the values of two weights, whose suitable values are set with an “automatic” choice algorithm. The outcomes of the tests are compared with both simulations and experimental results obtained by using a “classic” spline trajectory planning algorithm. The experimental tests are carried out by using an accelerometer mounted on a Cartesian robot.

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