High Precision Positioning and Rotation Angle Estimation of a Flatbed Truck Based on BDS and Vision
Xinli Yu, Yufei Ren, Xiaoxv Yin, Deqiang Meng, Haikuan Zhang
TL;DR
This paper presents a method using BDS and vision to precisely locate and estimate the rotation angle of flatbed trucks for automated forklift loading.
Contribution
A novel method combining BDS and vision for high-precision flatbed truck positioning and rotation angle estimation.
Findings
Endpoint positioning error was less than 3 cm.
Rotation angle estimation error was less than 0.3°.
Abstract
Centimeter-level localization and precise rotation angle estimation for flatbed trucks pose significant challenges in unmanned forklift automated loading scenarios. To address this issue, the study proposed a method for high-precision positioning and rotation angle estimation of flatbed trucks using the BeiDou Navigation Satellite System (BDS) and vision technology. First, an unmanned forklift equipped with a Time-of-Flight (ToF) camera and a dual-antenna mobile receiver for BDS positioning collected depth images and localization data near the front and rear endpoints of the flatbed. The Deep Dual-Resolution Network-23-slim (DDRNet-23-slim) model was used to segment the flatbed from the depth image and extract the straight lines at the edges of the flatbed using the Hough transform. The algorithm then computed the set of intersection points of the lines. A neighborhood feature vector…
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Taxonomy
TopicsImage and Object Detection Techniques · Robotics and Sensor-Based Localization · 3D Surveying and Cultural Heritage