Estimation of Excavator Manipulator Position Using Neural Network-Based Vision System The University of Alabama

Format:

Conference/Event

Author/Creator:

Xu, Xu, author.

Contributor:

Kim, Seonggon

Lee, Jae Y.

Yoon, Hwan-Sik

Conference Name:

SAE 2016 Commercial Vehicle Engineering Congress (2016-10-04 : Rosemont, Illinois, United States)

Language:

English

Physical Description:

1 online resource

Place of Publication:

Warrendale, PA SAE International 2016

Summary:

AbstractA 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

Notes:

Vendor supplied data

Publisher Number:

2016-01-8122

Access Restriction:

Restricted for use by site license