Product Assembly with Optimized Trajectory Planning

This project investigates the development of an energy-efficient trajectory optimisationsystem for industrial robotic arms, focusing on the Universal Robots (UR) Ur10e. Itaddresses the growing need for sustainable and user-accessible robotic solutions withinIndustry 5.0 by implementing a software framework that combines real-time data acquisition,symbolic optimisation with CasADi, and intuitive graphical user interfacesusing PySide6. The system enables non-expert users to define joint-space waypoints,optimise trajectories considering joint constraints and obstacle avoidance, and executethese paths with real-time energy monitoring via the RTDE protocol. Empirical evaluationsacross multiple motion scenarios demonstrate that optimised trajectories canreduce energy consumption without compromising execution reliability. The resultsvalidate the effectiveness of the speed trajectories in achieving energy savings, aligningwith theoretical models and practical observations. The solution offers a scalableand accessible tool for improving energy efficiency in robotic assembly tasks, therebycontributing to the broader goals of sustainable and human-centric automation.

Publication Details

Journal
University Library of Skövde (University of Skövde)
Published
2025-01-01
Primary Topic
Robot Manipulation and Learning
Type
article
Field-Weighted Citation Impact
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article

Product Assembly with Optimized Trajectory Planning

University Library of Skövde (University of Skövde)
Robot Manipulation and Learning
article

Product Assembly with Optimized Trajectory Planning

article en

Abstract

This project investigates the development of an energy-efficient trajectory optimisationsystem for industrial robotic arms, focusing on the Universal Robots (UR) Ur10e. Itaddresses the growing need for sustainable and user-accessible robotic solutions withinIndustry 5.0 by implementing a software framework that combines real-time data acquisition,symbolic optimisation with CasADi, and intuitive graphical user interfacesusing PySide6. The system enables non-expert users to define joint-space waypoints,optimise trajectories considering joint constraints and obstacle avoidance, and executethese paths with real-time energy monitoring via the RTDE protocol. Empirical evaluationsacross multiple motion scenarios demonstrate that optimised trajectories canreduce energy consumption without compromising execution reliability. The resultsvalidate the effectiveness of the speed trajectories in achieving energy savings, aligningwith theoretical models and practical observations. The solution offers a scalableand accessible tool for improving energy efficiency in robotic assembly tasks, therebycontributing to the broader goals of sustainable and human-centric automation.

University Library of Skövde (University of Skövde)
Affordable and clean energy
Openalex Percentile: Top 44%
Robot Manipulation and Learning
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Product Assembly with Optimized Trajectory Planning · University Library of Skövde (University of Skövde) (2025) | TGRS Research Map | TGRS