Pose Estimation for 3D Workpiece Grasping in Industrial Environment Based on Evolutionary Algorithm

2012 ◽  
Vol 68 (3-4) ◽  
pp. 293-306 ◽  
Author(s):  
Wei Liu ◽  
Tianshi Chen ◽  
Peng Wang ◽  
Hong Qiao
Keyword(s):  
Evolutionary Algorithm ◽  
Pose Estimation ◽  
Industrial Environment

KLT Bin Detection and Pose Estimation in an Industrial Environment

2020 ◽  
pp. 105-118
Author(s):  
Aleksei Beloshapko ◽  
Christian Knoll ◽  
Bilel Boughattas ◽  
Vladimir Korkhov
Keyword(s):  
Pose Estimation ◽  
Industrial Environment

scholarly journals A Novel Metric-Learning-Based Method for Multi-Instance Textureless Objects’ 6D Pose Estimation

2021 ◽  
Vol 11 (22) ◽  
pp. 10531
Author(s):  
Chenrui Wu ◽  
Long Chen ◽  
Shiqing Wu
Keyword(s):  
Pose Estimation ◽  
Real World ◽  
Graph Matching ◽  
Metric Learning ◽  
Intelligent Manufacturing ◽  
Fixed Size ◽  
Industrial Environment ◽  
Real World Applications ◽  
Dense Point ◽  
Detection Stage

6D pose estimation of objects is essential for intelligent manufacturing. Current methods mainly place emphasis on the single object’s pose estimation, which limit its use in real-world applications. In this paper, we propose a multi-instance framework of 6D pose estimation for textureless objects in an industrial environment. We use a two-stage pipeline for this purpose. In the detection stage, EfficientDet is used to detect target instances from the image. In the pose estimation stage, the cropped images are first interpolated into a fixed size, then fed into a pseudo-siamese graph matching network to calculate dense point correspondences. A modified circle loss is defined to measure the differences of positive and negative correspondences. Experiments on the antenna support demonstrate the effectiveness and advantages of our proposed method.

Model-Based Human Pose Estimation and Its Analysis Using Hausdorff Matching

2015 ◽  
Vol 2 (2) ◽  
pp. 51 ◽  
Author(s):  
Vivek Maik ◽  
Jinho Park ◽  
Daehee Kim ◽  
Joonki Paik
Keyword(s):  
Pose Estimation ◽  
Human Pose Estimation ◽  
Model Based ◽  
Its Analysis ◽  
Human Pose

Synchronous R-NSGA-II: An Extended Preference-Based Evolutionary Algorithm for Multi-Objective Optimization

Informatica ◽  
2015 ◽  
Vol 26 (1) ◽  
pp. 33-50 ◽  
Author(s):  
Ernestas Filatovas ◽  
Olga Kurasova ◽  
Karthik Sindhya
Keyword(s):  
Evolutionary Algorithm ◽  
Multi Objective Optimization ◽  
Nsga Ii ◽  
Multi Objective
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