Vision-based autonomous load handling for automated guided vehicles

Author

Varga, Rastislav ; Nedevschi, Sergiu

Author_Institution

Tech. Univ. of Cluj Napoca, Cluj-Napoca, Romania

fYear

2014

fDate

4-6 Sept. 2014

Firstpage

239

Lastpage

244

Abstract

The paper presents a method for automatically detecting pallets and estimating their position and orientation. For detection we use a sliding window approach with efficient candidate generation, fast integral features and a boosted classifier. Specific information regarding the detection task such as region of interest, pallet dimensions and pallet structure can be used to speed up and validate the detection process. Stereo reconstruction is employed for depth estimation by applying Semi-Global Matching aggregation with Census descriptors. Offline test results show that successful detection is possible under 0.5 seconds.

Keywords

automatic guided vehicles; image matching; image reconstruction; robot vision; stereo image processing; automated guided vehicles; census descriptors; depth estimation; orientation estimation; pallet detection; pallet dimensions; pallet structure; position estimation; semi-global matching aggregation; sliding window approach; stereo reconstruction; vision-based autonomous load handling; Cameras; Estimation; Feature extraction; Loading; Object detection; Standards; Stereo image processing; object detection; object recognition; stereo reconstruction;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Computer Communication and Processing (ICCP), 2014 IEEE International Conference on

Conference_Location

Cluj Napoca

Print_ISBN

978-1-4799-6568-7

Type

conf

DOI

10.1109/ICCP.2014.6937003

Filename

6937003