Vision-based autonomous load handling for automated guided vehicles
- 1 September 2014
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- p. 239-244
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
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