A pose estimation system based on deep neural network and ICP registration for robotic spray painting application
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Summary
A pose estimation system that is able to meet the robotic spray painting requirements is proposed and a deep convolutional neural network is proposed to determine the rough orientation of the target and guide the selection of model candidates accordingly thus preventing misalignment during registration.
- Type
- article
- Published
- 2019-05-30
- Cited by
- 27
- References
- 33
- OpenAlex
- https://openalex.org/W2947223272
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:189904292
Keywords
Artificial intelligence, Computer vision, Pose, Robustness (evolution), Iterative closest point
References
- On the importance of initialization and momentum in deep learning
- Advanced spraying task strategy for bicycle-frame based on geometrical data of workpiece
- RGB-D object recognition and pose estimation based on pre-trained convolutional neural network features
- Very Deep Convolutional Networks for Large-Scale Image Recognition
- SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation
- Novel integrated offline trajectory generation approach for robot assisted spray painting operation
- Automated tool trajectory planning of industrial robots for painting composite surfaces
- The Pascal Visual Object Classes (VOC) Challenge
- A Method for Registration of 3-D Shapes
- The MOPED framework: Object recognition and pose estimation for manipulation
- ImageNet: A large-scale hierarchical image database
- LabelMe: A Database and Web-Based Tool for Image Annotation
- Automated industrial robot path planning for spray painting process: A review
- A real-time position and posture measurement device for painting robot
- 3D is here: Point Cloud Library (PCL)
- Detection and fine 3D pose estimation of texture-less objects in RGB-D images
- A new point cloud slicing based path planning algorithm for robotic spray painting
- Fully Convolutional Networks for Semantic Segmentation
- A Method for Optimizing the Base Position of Mobile Painting Manipulators
- SegICP: Integrated deep semantic segmentation and pose estimation
Cited by
- A Smart Manufacturing Solution for Multi-Axis Dispenser Motion Planning in Mixed Production of Shoe Soles
- Grasping pose estimation for SCARA robot based on deep learning of point cloud
- Automatic monitoring of steel strip positioning error based on semantic segmentation
- Multi-View-Based Pose Estimation and Its Applications on Intelligent Manufacturing
- On the development of a collaborative robotic system for industrial coating cells
- An Adaptive Industrial Robot Spraying Planning and Control System
- Online 3-D Modeling of Complex Workpieces for the Robotic Spray Painting With Low-Cost RGB-D Cameras
- Fast 6D object pose estimation of shell parts for robotic assembly
- Integrated robotic measurement and machining technology for large castings
- Systematic Method for Evaluating the Performance of Three-Dimensional Optical Scanners by Structured Light Projection Applied to Ballistic Vests Tests
- Model-based Pose Measurement Using Structured Light Vision Sensor for a Target with Reflective Surface
- Fuzzy logic expert system with multi-objective optimization of carbon nanotube infused nanopaint surface characteristics analysis using IRB 1410 robot
- Reconstruction-Based Hand–Eye Calibration Using Arbitrary Objects
- An Online 3D Modeling Method for Pose Measurement under Uncertain Dynamic Occlusion Based on Binocular Camera
- A Bidirectional Guided Filter Used for RGB-D Maps
- Visual identification and pose estimation algorithms of nut tightening robot system
- Real-Time Bucket Pose Estimation Based on Deep Neural Network and Registration Using Onboard 3D Sensor
- Autonomous Trajectory Planning for Spray Painting on Complex Surfaces Based on a Point Cloud Model
- 6D Assembly Pose Estimation by Point Cloud Registration for Robot Manipulation
- Development of a Low-Cost Vision System for CAD-Based Guidance of Industrial Robots
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