English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

An obstacle detection method is proposed based on binocular stereo vision for manipulator. Firstly, images are preprocessed after camera calibration such as graying and distortion correction. Then, aiming at the defect that feature points are extracted mixed with many edge response points by traditional SIFT (Scale Invariant Feature Transform) algorithm, we propose wavelet transform to extract the edge points, and compare the edge points with feature points to further eliminate unstable feature points. Finally, the effectiveness of the algorithm is verified by obstacle detection and obstacle avoiding experiments. The results demonstrate that the improved SIFT algorithm can remove the edge responses that the DOG operator generates effectively, and improve the stability and anti-noise ability of SIFT algorithm compared with traditional SIFT algorithm.

Binocular Stereo Vision Based Obstacle Detection Method for Manipulator