A No-code Approach for Intuitive Robot Programming for Process-Aligned Surface Processing

This work introduces a novel method for the generation of process-aligned robotic pathways specifically designed for surface processing applications. The proposed approach integrates the interpretation of sensor data, computer vision algorithms, and process knowledge modeling to address the complexities inherent in robotic programming. To mitigate programming challenges, the method incorporates intuitive interaction techniques, including hand gestures and human-computer interaction (HCI), thereby facilitating the efficient generation of robotic paths. Additionally, it augments the user’s teaching experience by enabling the seamless deployment of the methodology in serial production settings, accommodating the variability of both workpieces and environmental conditions. The proposed framework ensures smooth integration of robotic systems into complex workflows by aligning robotic paths with the unique requirements of surface processing tasks.

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Publication Details

Published
2025-10-19
DOI
https://doi.org/10.1109/iros60139.2025.11246106
Primary Topic
Robot Manipulation and Learning
Type
article
Field-Weighted Citation Impact
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article

A No-code Approach for Intuitive Robot Programming for Process-Aligned Surface Processing

Jayanto Halim, Steffen Ihlenfeldt, Mohamad Bdiwi
Robot Manipulation and Learning
article

A No-code Approach for Intuitive Robot Programming for Process-Aligned Surface Processing

Jayanto Halim, Steffen Ihlenfeldt, Mohamad Bdiwi
article en

Abstract

This work introduces a novel method for the generation of process-aligned robotic pathways specifically designed for surface processing applications. The proposed approach integrates the interpretation of sensor data, computer vision algorithms, and process knowledge modeling to address the complexities inherent in robotic programming. To mitigate programming challenges, the method incorporates intuitive interaction techniques, including hand gestures and human-computer interaction (HCI), thereby facilitating the efficient generation of robotic paths. Additionally, it augments the user’s teaching experience by enabling the seamless deployment of the methodology in serial production settings, accommodating the variability of both workpieces and environmental conditions. The proposed framework ensures smooth integration of robotic systems into complex workflows by aligning robotic paths with the unique requirements of surface processing tasks.

Fraunhofer Institute for Machine Tools and Forming Technology (DE)
Openalex Percentile: Top 54%
Robot Manipulation and Learning
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