XAI-driven digital twin for cobot dynamic error compensation

Puthanveettil Madathil, Abhilash, Walker, Charlie, Luo, Xichun, Liu, Qi, Madarkar, Rajeshkumar and Qin, Yi (2024) XAI-driven digital twin for cobot dynamic error compensation. Procedia CIRP, 126. pp. 176-181.

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Abstract

Process and product fingerprints (FP) have been approved as effective parameters to reveal the principal contributing factors towards functionality in smart manufacturing processes. Though AI-driven methods outperform other approaches for fingerprint extraction, the lack of explainability in its black-box style predictions leads to misconceptions and trust issues among stakeholders. In this study, a novel explainable-AI (XAI) approach is proposed to identify mathematical fingerprint expressions by formulating them as graphs using the QLattice algorithm, inspired by path integral formulation. Here, the Qlattice model identifies explainable and human-comprehensible FP expressions for cobot dynamic error based on accelerometer signal features. The discovered symbolic model is subsequently applied to a digital twin which successfully tracked and compensated for dynamic errors autonomously in real time.

Item Type:	Article
Depositing User:	RED Unit Admin
Date Deposited:	16 Apr 2025 13:34
Last Modified:	16 Apr 2025 13:34
URI:	https://bnu.repository.guildhe.ac.uk/id/eprint/19713

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