Experimental Validation of Minimum Time-jerk Algorithms for Industrial Robots

In this paper, we present a minimum-time/jerk algorithm for trajectory planning and its experimental validation. The algorithm search for a trade-off between the need for a short execution time and the requirement of a sufficiently smooth trajectory, which is the well known necessary condition to limit the vibration during fast movements. The trade-off is achieved by adjusting the weight of two suitable functions, able to consider both the execution time and the squared-jerk integral along the whole trajectory. The main feature of this algorithm is its ability to smooth the trajectory's profile by adjusting the intervals between two consecutive via-points so that the overall time is minimally delayed. The practical importance of this technique lies in the fact that it can be implemented in any industrial manipulator without a hardware upgrade. The algorithm does not need for a dynamic model of the robot: only the mechanical constraints on the position, velocity and acceleration ranges have to be set a priori. The experimental proof is provided in this paper by comparing the results of the proposed algorithm with those obtained by adopting some classical algorithms.