机器人视觉SLAM研究进展

Q3 Computer Science
Hongxin Zhang, Hui Jin, Shaowei Ma
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引用次数: 0

摘要

SLAM在机器人、无人机、无人驾驶车辆的导航中发挥着重要的作用。定位精度将影响避障的精度。地图构建的质量直接影响后续路径规划和其他算法的性能。它是智能移动应用的核心算法。因此,机器人视觉slam具有很大的研究价值,将是未来重要的研究方向。本文通过对计算机视觉SLAM的最新进展和专利的回顾,为相关领域的研究者提供参考。从算法、创新和应用等方面分析了计算机视觉SLAM的专利和文献。其中,近十年来已获得专利30余项,发表文献近30篇。本文回顾了近10年来机器人视觉SLAM的研究进展,总结了其典型特征,特别是对视觉SLAM系统的前端部分进行了详细的描述,描述了每种方法的主要优缺点,分析了机器人视觉SLAM发展中存在的主要问题,展望了其发展趋势,最后讨论了机器人视觉SLAM技术的相关产品和专利研究现状及未来。机器人视觉SLAM可以比较环境的纹理信息,识别两种环境的差异,从而提高准确率。然而,目前的SLAM算法在快速运动和高动态环境中容易失效,大多数SLAM动作计划效率低下,并且VSLAM的图像特征太容易区分。此外,还应该发明更多的机器人视觉SLAM专利。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Recent Advances in Robot Visual SLAM
SLAM plays an important role in the navigation of robots, unmanned aerial vehicles, and unmanned vehicles. The positioning accuracy will affect the accuracy of obstacle avoidance. The quality of map construction directly affects the performance of subsequent path planning and other algorithms. It is the core algorithm of the intelligent mobile application. Therefore, robot vision slam has great research value and will be an important research direction in the future. By reviewing the latest development and patent of Computer Vision SLAM, this paper provides references to researchers in related fields. Computer Vision SLAM patents and literature were analyzed from the aspects of the algorithm, innovation, and application. Among them, there are more than 30 patents and nearly 30 pieces of literature in the past ten years. This paper reviews the research progress of robot visual SLAM in the last 10 years, summarizes its typical features, especially describes the front part of the visual SLAM system in detail, describes the main advantages and disadvantages of each method, analyses the main problems in the development of robot visual SLAM, prospects its development trend, and finally discusses the related products and patents research status and future of robot visual SLAM technology. The Robot Vision SLAM can compare the texture information of the environment and identify the difference between the two environments, thus improving accuracy. However, the current SLAM algorithm is easy to fail in fast motion and highly dynamic environments, most SLAM action plans are inefficient, and the image features of VSLAM are too distinguishable. Furthermore, more patents on the Robot Vision SLAM should also be invented.
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来源期刊
Recent Advances in Computer Science and Communications
Recent Advances in Computer Science and Communications Computer Science-Computer Science (all)
CiteScore
2.50
自引率
0.00%
发文量
142
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