Towards Optimized Parallel Robots for Human-Robot Collaboration by Combined Structural and Dimensional Synthesis

TL;DR

This work tackles the safety challenge of human–robot collaboration with parallel robots by embedding clamping and collision hazards into a combined structural and dimensional synthesis, solved via multi-objective PSO under hierarchical constraints. It introduces a kinetostatic framework that projects external contact forces onto drive torques for back-drivability and detectability, coupled with four objective functions $f_1$–$f_4$ to evaluate collision and mass effects during a reference trajectory. The main contributions are the derivation of the kinetostatic projection, the formulation of the four HRC objectives, and the demonstration that a Hexa 6-RUS parallel structure provides the best trade-off among clamping distance, detectability, and effective mass, as revealed by Pareto analyses in a pick-and-place scenario. The findings offer design guidelines for safer, faster HRC-enabled PRs and highlight the Hexa configuration as a practically favorable option, guiding subsequent drive-dimensioning and hardware-selection efforts for real-world deployment.

Abstract

Parallel robots (PR) offer potential for human-robot collaboration (HRC) due to their lower moving masses and higher speeds. However, the parallel leg chains increase the risks of collision and clamping. In this work, these hazards are described by kinematics and kinetostatics models to minimize them as objective functions by a combined structural and dimensional synthesis in a particle-swarm optimization. In addition to the risk of clamping within and between kinematic chains, the back-drivability is quantified to theoretically guarantee detectability via motor current. Another HRC-relevant objective function is the largest eigenvalue of the mass matrix formulated in the operational-space coordinates to consider collision effects. Multi-objective optimization leads to different Pareto-optimal PR structures. The results show that the optimization leads to significant improvement of the HRC criteria and that a Hexa structure (6-RUS) is to be favored concerning the objective functions and due to its simpler joint structure.

Figures (7)

• Figure 1: (a) Serial and parallel robot. The contribution of this work are: (b) Clamping- and collision scenarios, (c) clamping hazards in a Pareto diagram, and (d) optimal parallel robot (symbolic image) with minimal clamping hazards, which complies with the constraints of the impermissible space, the planned interaction space, and the allowed installation space.
• Figure 2: Overall procedure for the dimensional synthesis of a robot using hierarchical constraints, mod. from SchapplerOrt2020
• Figure 3: Pareto diagrams of the results with only Pareto-dominant solutions regarding the respective criteria. Solutions exceeding the thresholds on optimization criteria are plotted transparently. Good values are located in the lower left of the diagrams.
• Figure 4: Kinematic sketches of parallel robots with different leg chains, based on Fig. \ref{['fig:ergebnisse']}(a); performance shown in Fig. \ref{['fig:radarchart']}(a)
• Figure 5: Radar charts of the five objective functions with the five parallel-robot structures: (a) Solutions from Fig. \ref{['fig:ergebnisse_roboter']} as compromise of $f_3$ and $f_4$, (b) from the respective maximum of $f_1$, (c) maximum of $f_3$, and (d) minimum of $f_4$; best values are on the outside.