Criteria

Text:
Author:
Display:

Results

Viewing 1 of 1
2016-09-27
Technical Paper
2016-01-8122
Jiaqi Xu, Hwan-Sik Yoon, Jae Y. Lee, Seonggon Kim
Abstract 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.
Viewing 1 of 1