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In this research, six brands of soft drinks are decided to be picked up by a robot with a monocular Red Green Blue (RGB) camera. The drinking bottles need to be located and classified with brands before being picked up. The Mask Regional Convolutional Neural Network (R-CNN), a mask generation network improved from Faster R-CNN, is trained with common object in contest datasets to detect and generate the mask on the bottles in the image. The Inception v3 is selected for the brand classification task. Around 200 images are taken or found at first; then, the images are augmented to 1500 images per brands by using random cropping and perspective transform. The result shows that the masked image can be labeled with its brand name with at least 85% accuracy in the experiment.Continue reading Image Processing for Picking Task of Random Ordered PET Drinking Bottles
This article describes forward kinematics of the six degrees of freedom manipulator and its geometric inverse kinematics geometric.
The algorithm described in this article has not been strictly tested. Take your own risk while using it
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The robot structure is shown in the figure below:
This article describes the related information of robot kinematics, including the solution of rotation matrix, vector and mechanical arm pose, and using C# to describe the relevant algorithm.
The rotation matrix in linear algebra is used to make the vector rotate in the Euler space.
In robotics, the rotation matrix is used to solve the posture (orientation) of the robot joint. In three-dimensional space, the eigenvalue of the rotation matrix is 1.