Recognition and Pose Estimation of Auto Parts for an Autonomous Spray Painting Robot

Lin, Weiyang; Anwar, Ali; Zhan, Lihua; Tong, Mingsi; Qiu, Jianbin; Gao, Huijun

doi:10.1109/tii.2018.2882446

Cited by 51 publications

(17 citation statements)

References 37 publications

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“…L. et al developed an anthromorphical robot for handling complex geometrical spray-painting paths and for precise spray painting applications. 24 Several researchers 21,[25][26][27][28] identified that for handling the vast demands of spray-painting applications in industries, robot trajectory 29 had to be optimized using principal component analysis and pose estimation. Factors such as transfer rate, gun travel speed, pressure, and surface preparation play a crucial role in spray painting applications.…”

Section: Introductionmentioning

confidence: 99%

Fuzzy logic expert system with multi-objective optimization of carbon nanotube infused nanopaint surface characteristics analysis using IRB 1410 robot

Jakkula

Sethuramalingam

2022

Proceedings of the Institution of Mechanical Engineers, Part C:

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In this investigative study, the Taguchi design (L9) of experiments with TOPSIS multi-objective optimization is used for the robot nanopainting. The optimization objective is to maximize the film glue individually and minimize the surface blemishes and film thickness by varying the IRB 1410 robot painting parameters, such as the robot speed, pressure, and distance. The multi-wall carbon nanotube is infused into the paint materials using the ultrasonication process, and the mechanical properties are analysed with a comparison to regular paint materials. The virtual robot cycle time analysis is carried out for three different robot pathway patterns, namely linear, zig-zag, and circular. It is then compared with real-time experimental robot nanopaint on cold rolled close annealing steel materials. The obtained results show that surface roughness and thickness are minimized by 54% and 33.4%, respectively, using the robot nano spray coating when compared with regular spray coating. The film adhesive of robot Nano spray coating is maximized by 2.8% more than normal spray coating. A fuzzy logic expert system model is used to evaluate the surface finish characteristics of the nanopaint surface with low prediction error and with 89.2% confidence level. Heat transfer analysis of the robot nano-coated substrate is compared with that of the robot normal-coated substrate.

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Section: Introductionmentioning

confidence: 99%

Fuzzy logic expert system with multi-objective optimization of carbon nanotube infused nanopaint surface characteristics analysis using IRB 1410 robot

Jakkula

Sethuramalingam

2022

Proceedings of the Institution of Mechanical Engineers, Part C:

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“…A S a prerequisite for plenty of application scenarios such as intelligent robot, aerospace, industry, the real-time and accurate 3D attitude angle estimation has attracted tremendous attention [1], [2]. Recent years have witnessed the flourishing of attitude angle estimation, which could be divided into the monocular vision based, the binocular vision based and the multi-vision based methods, according to the number of cameras [3], [4].…”

Section: Introductionmentioning

confidence: 99%

FADN: Fully Connected Attitude Detection Network Based on Industrial Video

Yang

Meng

Jiang

et al. 2021

IEEE Trans. Ind. Inf.

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In 3D attitude angle estimation, monocular visionbased methods are often utilized for the advantages of short-time and high efficiency. However, the limitations of these methods lie in the complexity of the algorithm and the specificity of the scene, which needs to match the characteristics of the cooperation object and the scene. We propose a fully connected attitude detection network (FADN) which combines neural network and traditional algorithms for 3D attitude angle estimation. FADN provides a whole process from the input of a single frame image in the industrial video stream to the output of the corresponding 3D attitude angle estimation. Benefiting from the end-to-end estimation framework, FADN avoids tedious matching algorithms and thus has certain portability. A series of comparative experiments based on the rendering software 3D Studio Max (3d Max) have been carried out to evaluate the performance of FADN. The experimental results show that FADN has high estimation accuracy and fast running speed. At the same time, the simulation results reliably prove the feasibility of FADN, and also promote the research in real scenarios.

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“…In this paper, inspired by the solutions of the pose estimation for humans [22], human head [23], and rigid objects [24], we devise methods for the UAV 6D pose estimation with high accuracy, strong robustness, and real-time capability for autonomous landing guidance based on the ground vision system. A monocular vision-based solution and a stereo vision-based solution are presented in this paper.…”

Section: Introductionmentioning

confidence: 99%

Learning-Type Anchors-Driven Pose Estimation for the Autolanding Fixed-Wing UAVs

Tang,

Shen,

Xiang

et al. 2021

Preprint

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<p>We propose a learning-type anchors-driven real-time pose estimation method for the autolanding fixed-wing unmanned aerial vehicle (UAV). The proposed method enables online tracking of both position and attitude by the ground stereo vision system in the Global Navigation Satellite System denied environments. A pipeline of convolutional neural network (CNN)-based UAV anchors detection and anchors-driven UAV pose estimation are employed. To realize robust and accurate anchors detection, we design and implement a Block-CNN architecture to reduce the impact of the outliers. With the basis of the anchors, monocular and stereo vision-based filters are established to update the UAV position and attitude. To expand the training dataset without extra outdoor experiments, we develop a parallel system containing the outdoor and simulated systems with the same configuration. Simulated and outdoor experiments are performed to demonstrate the remarkable pose estimation accuracy improvement compared with the conventional Perspective-N-Points solution. In addition, the experiments also validate the feasibility of the proposed architecture and algorithm in terms of the accuracy and real-time capability requirements for fixed-wing autolanding UAVs.</p>

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Recognition and Pose Estimation of Auto Parts for an Autonomous Spray Painting Robot

Cited by 51 publications

References 37 publications

Fuzzy logic expert system with multi-objective optimization of carbon nanotube infused nanopaint surface characteristics analysis using IRB 1410 robot

Fuzzy logic expert system with multi-objective optimization of carbon nanotube infused nanopaint surface characteristics analysis using IRB 1410 robot

FADN: Fully Connected Attitude Detection Network Based on Industrial Video

Learning-Type Anchors-Driven Pose Estimation for the Autolanding Fixed-Wing UAVs

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