摘要翻译：
仓储物流机器人将在不同的仓库环境中工作。为了使机器人能够在不修改现有仓库的情况下更快地感知环境和规划路径，我们采用单目摄像机实现了一个高效的机器人集成系统。地图绘制和路径规划是本文的两个主要任务。采用直接法视觉里程法进行定位，计算出环境中主要障碍物的三维位置。利用所占网格地图描述地形，将三维点投影到机器人运动平面上，从而确定每个网格的可达性。基于地形信息，采用优化的A*算法进行路径规划。最后，根据定位和规划控制机器人进行路径跟踪。我们还开发了一个路径跟踪机器人原型。仿真和实验结果验证了所提方法的有效性和可靠性。
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英文标题：
《Wheeled Robots Path Planing and Tracking System Based on Monocular
  Visual SLAM》
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作者：
Ziqiang Wang and Hegen Xu and Youwen Wan
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最新提交年份：
2018
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分类信息：

一级分类：Computer Science        计算机科学
二级分类：Robotics        机器人学
分类描述：Roughly includes material in ACM Subject Class I.2.9.
大致包括ACM科目I.2.9类的材料。
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一级分类：Electrical Engineering and Systems Science        电气工程与系统科学
二级分类：Image and Video Processing        图像和视频处理
分类描述：Theory, algorithms, and architectures for the formation, capture, processing, communication, analysis, and display of images, video, and multidimensional signals in a wide variety of applications. Topics of interest include: mathematical, statistical, and perceptual image and video modeling and representation; linear and nonlinear filtering, de-blurring, enhancement, restoration, and reconstruction from degraded, low-resolution or tomographic data; lossless and lossy compression and coding; segmentation, alignment, and recognition; image rendering, visualization, and printing; computational imaging, including ultrasound, tomographic and magnetic resonance imaging; and image and video analysis, synthesis, storage, search and retrieval.
用于图像、视频和多维信号的形成、捕获、处理、通信、分析和显示的理论、算法和体系结构。感兴趣的主题包括：数学，统计，和感知图像和视频建模和表示；线性和非线性滤波、去模糊、增强、恢复和重建退化、低分辨率或层析数据；无损和有损压缩编码；分割、对齐和识别；图像渲染、可视化和打印；计算成像，包括超声、断层和磁共振成像；以及图像和视频的分析、合成、存储、搜索和检索。
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英文摘要：
  Warehouse logistics robots will work in different warehouse environments. In order to enable robots to perceive environment and plan path faster without modifying existing warehouses, we uses monocular camera to achieve an efficient robot integrated system. Mapping and path planning the two main tasks presented in this paper. The direct method visual odometry is applied to localize, and the 3D position of major obstacles in the environment is calculated. We describe the terrain with occupied grid map, the 3D points are projected onto the robot motion plane, thus accessibility of each grid is determined. Based on the terrain information, the optimized A* algorithm is used for path planning. Finally, according to localization and planning, we control the robot to track path. We also develop a path-tracking robot prototype. Simulation and experimental results verify the effectiveness and reliability of the proposed method.
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PDF链接：
https://arxiv.org/pdf/1807.06303