Deep Convolution Neural Networks for the Classification of Robot Execution Failures ; Article #: ; Date of Conference: 05-07 July 2019 ; Date Added to IEEE Xplore: ...
Key Words: Deep learning, manipulator, failure diagnosis, convolution neural network, classification ... for classification of robot execution failures in 2014.
In this paper, manipulator fault classifier based on DCNNs is proposed, and the sensor data from force and torque sensors are preprocessed and reconstructed ...
The proposed manipulator fault classifier is useful for enhancing the executive capability of manipulators, and the designed classifier can effectively ...
People also ask
What are deep convolutional neural networks?
What are the issues in training a convolutional neural network model for image classification?
What is a convolutional neural network in deep learning?
If this approach fails to deliver extra accuracy, then replacing standard fire modules with extended fire modules can increase the quality of the network.
The deep convolutional neural networks (DCNN) are used in [21] to detect robot manipulator execution failures using sensor data from force and torque sensors.
In most robot system faults, sensor and actuator malfunction are the main causes of robot system failure. Therefore, diagnosis for the sensors and actuators is ...
... robot execution failures based on neural networks. Real data consisting of ... failure classification for assembly with self-tapping threaded fastenings using ...
There exists a neural network that does not make avoidable mistakes. Glorot ... Imagenet classification with deep convolutional neural networks.
Feb 2, 2023 · The results showed that when SMIS fails, the failure behavior can easily lead SMIS into chaos through the propagation of an interdependent ...