Research on Informed-RRT* with Improved Initial Solution

Zhao, Yang; Liu, Yiyang; Gao, Hongwei; Yan, Shuaihua

doi:10.1109/icmsp55950.2022.9859229

Cited by 3 publications

(1 citation statement)

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“…Stereo correction [30] utilizes the internal and external parameters of binocular calibration, as well as the binocular relative position relationship, to eliminate aberrations and align the lines for the left and right views, respectively. In this paper, the Bouguet correction method [31] is used to minimize the number of re-projections for each of the left and right images, and the corrected image is shown in Figure 5.…”

Section: Stereo Correctionmentioning

confidence: 99%

Binocular Vision-Based Pole-Shaped Obstacle Detection and Ranging Study

Cai,

Zhou,

Wang

et al. 2023

Applied Sciences

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(1) Background: In real road scenarios, various complex environmental conditions may occur, including bright lights, nighttime, rain, and snow. In such a complex environment for detecting pole-shaped obstacles, it is easy to lose the feature information. A high rate of leakage detection, false positives, and measurement errors are generated as a result. (2) Methods: The first part of this paper utilizes the improved YOLOv5 algorithm to detect and classify pole-shaped obstacles. Then, the identified target frame information is combined with binocular stereo matching to obtain more accurate distance information. (3) Results: The experimental results demonstrate that this method achieves a mean average precision (mAP) of 97.4% for detecting pole-shaped obstacles, which is 3.1% higher than the original model. The image inference time is only 1.6 ms, which is 1.8 ms faster than the original algorithm. Additionally, the model size is only 19.0 MB. Furthermore, the range error of this system is less than 7% within the range of 3–15 m. (4) Conclusions: Therefore, the algorithm not only achieves real-time and accurate identification and classification but also ensures precise measurement within a specific range. Meanwhile, the model is lightweight and better suited for deploying sensing systems.

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Section: Stereo Correctionmentioning

confidence: 99%