Cartesian trajectory planners for robotic applications

Abstract

Trajectories in the operational space, when conceived for manipulators with more then three degrees of freedom, impose the adoption of both a position and an orientation primitive for the end-effector. The planning complexity increases if smoothness represents one of the motion requirements and the trajectory is obtained through the combination of several via points. In this eventuality, vibrations and mechanical solicitations can be reduced by avoiding motion stops when reaching control points. Good tracking performances can be conversely achieved by guaranteeing jerk-continuous reference signals for the actuators. The planners proposed in this thesis allow the smart generation of smooth trajectories. As experimentally proved in the work, the novel planning primitives are characterized by very short computational times.