Estimation of Excavator Manipulator Position Using Neural Network-Based Vision System 2016-01-8122
A neural network-based computer vision system is developed to estimate position of an excavator manipulator in real time. A camera is used to capture images of a manipulator, and the images are down-sampled and used to train a neural network. Then, the trained neural network can estimate the position of the excavator manipulator in real time. To study the feasibility of the proposed system, a webcam is used to capture images of an excavator simulation model and the captured images are used to train a neural network. The simulation results show that the developed neural network-based computer vision system can estimate the position of the excavator manipulator with an acceptable accuracy.
Citation: Xu, J., Yoon, H., Lee, J., and Kim, S., "Estimation of Excavator Manipulator Position Using Neural Network-Based Vision System," SAE Technical Paper 2016-01-8122, 2016, https://doi.org/10.4271/2016-01-8122. Download Citation
Author(s):
Jiaqi Xu, Hwan-Sik Yoon, Jae Y. Lee, Seonggon Kim
Affiliated:
The University of Alabama, Volvo Construction Equipment
Pages: 9
Event:
SAE 2016 Commercial Vehicle Engineering Congress
ISSN:
0148-7191
e-ISSN:
2688-3627
Also in:
The Best of COMVEC 2016 Select Technical Papers from the SAE Commercial Vehicle Engineering Congress-PT-180
Related Topics:
Neural networks
Simulation and modeling
Imaging and visualization
Railway vehicles and equipment
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