| 基于改进HOG算法的AGV小车避障研究 |
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| 引用本文： | 万 伟,刘子龙.基于改进HOG算法的AGV小车避障研究[J].教育技术导刊,2020,19(3):6-9. |
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| 作者姓名： | 万 伟 刘子龙 |
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| 作者单位： | 上海理工大学 光电信息与计算机工程学院，上海 200093 |
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| 基金项目： | 国家自然科学基金项目（61603255） |
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| 摘 要： | 为解决激光传感器等避障装置难以解决爆炸性危险环境下的防爆问题，提出一种基于机器视觉的AGV小车避障解决方案。磁导航AGV小车在工作中路径相对固定，主要针对来回走动的工人进行检测，进而实现减速或制动。为实现高精确度下实时检测，采用改进HOG算法，结合线性支持向量机实现更快和更可靠的分类。实验证明，该方法识别率达到92.84%，漏检率4%，其准确度和实时性基本满足危险环境下的行人检测要求。
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| 关 键 词： | AGV 行人检测 HOG 线性支持向量机 危险环境 |
| 收稿时间： | 2019-04-28 |
Research on AGV Vehicle Obstacle Avoidance Based on Improved HOG Algorithm |
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| WAN Wei,LIU Zi-long.Research on AGV Vehicle Obstacle Avoidance Based on Improved HOG Algorithm[J].Introduction of Educational Technology,2020,19(3):6-9. |
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| Authors: | WAN Wei LIU Zi-long |
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| Institution: | School of Optical Electrical and Computer Engineering，University of Shanghai for Science and Technology， Shanghai 200093， China |
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| Abstract: | In order to solve the problem of explosion-proof in the explosion-hazard environment， a machine vision-based AGV trolley obstacle avoidance solution is proposed. The magnetic navigation AGV trolley has a relatively fixed path during work， and is mainly used for detecting and moving around the working path to realize deceleration or braking. To ensure real-time detection with high accuracy， the improved directional gradient histogram （HOG） algorithm and linear support vector machine （LSVM） are used to achieve faster and more reliable classification. The experiment proves that the recognition rate of the method reaches 92.84%， and the missed detection rate is 4%. Its accuracy and real-time performance can basically meet the pedestrian detection in industrial hazardous environment. |
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| Keywords: | AGV pedestrian detection HOG Linear support vector machine dangerous environment |
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