Temporal Coupling of Dynamical Movement Primitives for Constrained Velocities and Accelerations
Albin Dahlin, Yiannis Karayiannidis
Abstract
The framework of Dynamical Movement Primitives (DMPs) has become a popular method for trajectory generation in robotics. Most robotic systems are subject to saturation and/or kinematic constraints on motion variables, but DMPs do not inherently encode constraints and this may lead to poor tracking performance. Temporal coupling (online temporal scaling) of DMPs represents a possible way for handling constrained systems. This letter presents a temporal coupling for DMPs to handle velocity and acceleration constraints for the generated trajectory. A novel filter is presented based on a potential function which proactively scales the trajectory before reaching the acceleration limits. In this way, the velocities and accelerations remain within the limits even for trajectories with aggressive accelerations and stricter bounds. The performance of the proposed method is demonstrated by means of simulations and experiments on a UR10 robot.