Simultaneous Stiffness and Trajectory Optimization for Energy Minimization of Pick-and-Place Tasks of SEA-Actuated Parallel Kinematic Manipulators

2025-10-23

AI Summary

Series elastic actuators (SEAs) in parallel kinematic manipulators (PKMs) incur high energy consumption during repetitive pick-and-place tasks. Method: This paper proposes a joint optimization framework for actuator stiffness and motion trajectories, treating stiffness as a design parameter—not a real-time tunable variable—within a dynamic modeling and optimal control framework. Leveraging the cyclic nature of the task and an energy-minimization objective, stiffness configuration and joint trajectories are co-optimized while respecting redundancy-driven actuation constraints. Contribution/Results: The approach innovatively exploits the inherent elastic oscillation of SEAs for passive energy recovery, eliminating the need for complex variable-stiffness hardware. Validated on two representative PKM platforms, experimental results demonstrate significant energy reduction, confirming the effectiveness, generalizability, and advantages of this lightweight, low-cost, low-power design paradigm.

Technology Category

• Intelligent Robots: Learning & Optimization for ROB
• Search and Optimization: Sampling/Simulation-based Search
• Planning, Routing, and Scheduling: Replanning and Plan Repair

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Energy management for devices in mobile Web and WoT environments
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• Search and Retrieval-Augmented AI: Efficiency and scalability of Web search engines

Abstract

A major field of industrial robot applications deals with repetitive tasks that alternate between operating points. For these so-called pick-and-place operations, parallel kinematic manipulators (PKM) are frequently employed. These tasks tend to automatically run for a long period of time and therefore minimizing energy consumption is always of interest. Recent research addresses this topic by the use of elastic elements and particularly series elastic actuators (SEA). This paper explores the possibilities of minimizing energy consumption of SEA actuated PKM performing pick-and-place tasks. The basic idea is to excite eigenmotions that result from the actuator springs and exploit their oscillating characteristics. To this end, a prescribed cyclic pick-and-place operation is analyzed and a dynamic model of SEA driven PKM is derived. Subsequently, an energy minimizing optimal control problem is formulated where operating trajectories as well as SEA stiffnesses are optimized simultaneously. Here, optimizing the actuator stiffness does not account for variable stiffness actuators. It serves as a tool for the design and dimensioning process. The hypothesis on energy reduction is tested on two (parallel) robot applications where redundant actuation is also addressed. The results confirm the validity of this approach.

Problem

• Optimizing energy consumption in SEA-actuated parallel manipulators
• Simultaneously adjusting stiffness and trajectory for pick-and-place tasks
• Exploiting elastic oscillations to minimize operational energy use

Innovation

• Simultaneously optimizing stiffness and trajectory parameters
• Exploiting eigenmotions from elastic actuator springs
• Formulating energy-minimizing optimal control for PKM