Trajectory planning and active dynamic balancing for highly dynamic handling tasks, a comparative study

Abstract

To achieve both energy efficiency and high positioning accuracy, dynamic manipulation tasks such as those found in the packaging industry require lightweight, rigid robotic systems with a high payload-to-weight ratio. Parallel robots are well suited to these requirements due to their kinematic design, with a base-mounted drive system that minimizes inertia. Among them, the Delta robot is the most widely used in such applications. In many industrial applications, it is necessary to operate the robot at reduced speeds or include dwell times in the motion planning to allow vibrations to subside. This helps to maintain accuracy and prevents fatigue and wear of mechanical components. While many studies investigate individual vibration reduction methods, a comprehensive comparison, both theoretical and experimental, is missing, particularly in the context of highly dynamic tasks. This publication addresses this gap by presenting a theoretical analysis of two vibration reduction strategies: trajectory smoothing and dynamic balancing. Furthermore, an experimental validation using a Delta robot in a representative pick-and-place scenario is provided to illustrate the effectiveness, trade-offs, and challenges associated with applying these methods in real-world scenarios.