Scalable Network and Adaptive Refinement Module for 6D Pose Estimation of Diverse Industrial Components

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The estimation of the 6D pose of industrial components is essential for smart manufacturing. Especially for complex units that require intensive manual operations, such as a concentrator photovoltaics solar panel, accurate spatial localization provides visual aids for industrial automation. In this paper, we propose an accurate and scalable framework to address the dimensional variability of industrial components and tackle practical implementation issues. First, we use the scalable architecture EfficientNet as the backbone coupled with an enhanced feature pyramid network to estimate the object’s pose. By introducing vertical and horizontal connections of shallow layers, the feature extraction of small objects is optimized for better detection accuracy. Second, leveraging the reliable 2D detection results and geometry information, an adaptive pose refinement module is designed to adjust the estimated 6D pose. The scaling of the backbone network and the computational complexity of refined modules are uniformly adjusted via a shared hyperparameter, resulting in a globally scalable framework. In terms of the pose estimation accuracy, the effectiveness of the refinement module and the real-time performance, validations are conducted both on the LINEMOD dataset and our customized datasets comprising of objects from the industrial photovoltaic system. Additionally, to further illustrate the effectiveness of the proposed method, a precision parallel robot is employed to validate the accuracy of real-time object pose tracking.
Original languageEnglish
Title of host publicationIEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2024)
PublisherIEEE
Publication statusAccepted/In press - 30 Jun 2024
EventIEEE/RSJ International Conference on Intelligent Robots and Systems 2024 - ADNEC, Abu Dhabi, United Arab Emirates
Duration: 14 Oct 202418 Oct 2024
https://iros2024-abudhabi.org/

Conference

ConferenceIEEE/RSJ International Conference on Intelligent Robots and Systems 2024
Abbreviated titleIROS 2024
Country/TerritoryUnited Arab Emirates
CityAbu Dhabi
Period14/10/2418/10/24
Internet address

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