| 1. |
- Jia, Qidong, et al.
(författare)
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Microbial-type terpene synthase genes occur widely in nonseed land plants, but not in seed plants
- 2016
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Ingår i: Proceedings of the National Academy of Sciences of the United States of America. - : Proceedings of the National Academy of Sciences. - 0027-8424 .- 1091-6490. ; 113:43, s. 12328-12333
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Tidskriftsartikel (refereegranskat)abstract
- The vast abundance of terpene natural products in nature is due to enzymes known as terpene synthases (TPSs) that convert acyclic prenyl diphosphate precursors into a multitude of cyclic and acyclic carbon skeletons. Yet the evolution of TPSs is not well understood at higher levels of classification. Microbial TPSs from bacteria and fungi are only distantly related to typical plant TPSs, whereas genes similar to microbial TPS genes have been recently identified in the lycophyte Selaginella moellendorffii. The goal of this study was to investigate the distribution, evolution, and biochemical functions of microbial terpene synthase-like (MTPSL) genes in other plants. By analyzing the transcriptomes of 1,103 plant species ranging from green algae to flowering plants, putative MTPSL genes were identified predominantly from nonseed plants, including liverworts, mosses, hornworts, lycophytes, and monilophytes. Directed searching for MTPSL genes in the sequenced genomes of a wide range of seed plants confirmed their general absence in this group. Among themselves, MTPSL proteins from nonseed plants form four major groups, with two of these more closely related to bacterial TPSs and the other two to fungal TPSs. Two of the four groups contain a canonical aspartate-rich "DDxxD" motif. The third group has a "DDxxxD" motif, and the fourth group has only the first two "DD" conserved in this motif. Upon heterologous expression, representative members from each of the four groups displayed diverse catalytic functions as monoterpene and sesquiterpene synthases, suggesting these are important for terpene formation in nonseed plants.
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| 2. |
- Zhang, Yinlong, et al.
(författare)
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3D-SWiM : 3D vision based seam width measurement for industrial composite fiber layup in-situ inspection
- 2023
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Ingår i: Robotics and Computer-Integrated Manufacturing. - : Elsevier BV. - 0736-5845 .- 1879-2537. ; 82
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Tidskriftsartikel (refereegranskat)abstract
- Industrial composite fiber has been widely used in the high-end manufacturing because of its superior stiffness and strength. To ensure the quality of composite fiber placement in making high-end and lightweight aerospace products, it needs reliable composite fiber layup in-situ inspection. An accurate seam width measurement is an indispensable procedure during the layup inspection. However, the traditional seam measurements may fail in presence of surface curvature variance, curved edges between sheets, to name a few. This paper intentionally designs a novel 3D vision based Seam Width Measurement for Industrial Composite Fiber Layup In-situ Inspection (called 3D-SWiM). It aims to address three major challenges in measuring the seam width between the composite fiber sheets, namely, seam region over-segmentation, failures on region of interests (ROI) seam detection, seam width measurement inconsistency. Firstly, the region growing with semantic refinement is designed for 3D point cloud clustering, to overcome over-segmentation on seam regions. Afterwards, the gridding model with edge discrimination is applied to extract the 3D potential candidates in the edge areas. Eventually, we use the cubic B-spline fitting model to describe the seam region curves and the improved particle swarm optimization model to estimate the minimum and maximum distance between the seam edges. 3D-SWiM has been evaluated extensively on the developed composite fiber layup platform. The comparisons with the state-of-the-art methods (such as HT and GFM) on the region-of-interest segmentation, seam extraction and seam width measurement have been performed and the experimental results prove the competitive performance in composite fiber layup in-situ inspections.
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| 3. |
- Zhang, Yinlong, et al.
(författare)
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GCMVF-AGV : Globally Consistent Multiview Visual-Inertial Fusion for AGV Navigation in Digital Workshops
- 2023
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Ingår i: IEEE Transactions on Instrumentation and Measurement. - : Institute of Electrical and Electronics Engineers (IEEE). - 0018-9456 .- 1557-9662. ; 72
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Tidskriftsartikel (refereegranskat)abstract
- An accurate and globally consistent navigation system is crucial for estimating the positions and attitudes of automated guided vehicles (AGVs) in digital workshops. A promising navigation technology for this purpose is tightly coupled visual-inertial fusion, which offers advantages such as quick response (QR), absolute scale, and accuracy. However, existing visual-inertial fusion systems have limitations, including long-term drift, tracking failures in textureless or poorly illuminated environments, and a lack of absolute references. To create a reliable and consistent AGV navigation framework and correct for long-term drift, we have designed a novel framework, globally consistent multiview visual-inertial fusion for AGV navigation (GCMVF-AGV). This framework uses a downward-looking QR vision sensor and a forward-looking visual-inertial sensor together to estimate AGV poses in real time. The downward camera provides absolute AGV positions and attitudes with reference to the global workshop frame. Furthermore, long-term visual-inertial drift, inertial biases, and velocities are periodically compensated between spatial intervals of QR codes by minimizing visual-inertial residuals with the rigid constraints of absolute poses estimated from the downward visual measurements. We have evaluated the proposed method on the developed AGV navigation platform, and experimental results demonstrate the position and attitude errors of less than 0.05 m and 2 degrees, respectively.
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| 4. |
- Zhang, Yinlong, et al.
(författare)
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Monocular Visual-Inertial and Robotic-Arm Calibration in a Unifying Framework
- 2022
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Ingår i: IEEE/CAA journal of automatica sinica. - : Institute of Electrical and Electronics Engineers (IEEE). - 2329-9266. ; 9:1, s. 146-159
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Tidskriftsartikel (refereegranskat)abstract
- Reliable and accurate calibration for camera, inertial measurement unit (IMU) and robot is a critical prerequisite for visual-inertial based robot pose estimation and surrounding environment perception. However, traditional calibrations suffer inaccuracy and inconsistency. To address these problems, this paper proposes a monocular visual-inertial and robotic-arm calibration in a unifying framework. In our method, the spatial relationship is geometrically correlated between the sensing units and robotic arm. The decoupled estimations on rotation and translation could reduce the coupled errors during the optimization. Additionally, the robotic calibration moving trajectory has been designed in a spiral pattern that enables full excitations on 6 DOF motions repeatably and consistently. The calibration has been evaluated on our developed platform. In the experiments, the calibration achieves the accuracy with rotation and translation RMSEs less than 0.7 degrees and 0.01 m, respectively. The comparisons with state-of-the-art results prove our calibration consistency, accuracy and effectiveness.
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