仔细考虑选项后，适合您的项目 - 听起来像地面上的移动机器人 - 可能是使用称为SLAM的机器人导航技术。
以下是参考SLAM的论文的引用：“在某些方法中，可导航地面检测的问题与定位任务一起解决.Perez-Yus使用RANSAC算法在人造室内场景中分割平面，等待密集的3D点
云”。
“这种方法不仅可以提取地面，还可以提升或下降楼梯，并通过视觉测距来确定用户的位置和方向.Lee还结合了视觉测距和基于特征的metri-拓扑同时定位和制图（SLAM）
）进行可穿越性分析“。
该论文发表于2016年11月，题目是“扩大对视觉障碍者的RealSense可穿越区域的检测”。
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5134613/
你可以通过谷歌搜索'os kinetic slam'找到有关使用SLAM和ROS Kinetic的信息。
如果您的项目可以使用OpenCV，ORB-SLAM2也是SLAM系统的一个非常值得推荐的选择。
GitHub - raulmur / ORB_SLAM2：用于单目，立体和RGB-D相机的实时SLAM，具有环路检测和重新定位...
以上来自于谷歌翻译
以下为原文
Having carefully considered the options, a good fit for your project - which sounds like a moving robot on the ground - may be to use the robotics navigation technique called SLAM.
Here is a quote from a paper that references SLAM: "In some approaches, the problem of navigable ground detection is addressed in conjunction with localization tasks. Perez-Yus used the RANSAC algorithm to segment planes in human-made indoor scenarios pending dense 3D point clouds".
"The approach is able to extract not only the ground but also ascending or descending stairs, and to determine the position and orientation of the user with visual odometry. Lee also incorporated visual odometry and feature-based metri-topological simultaneous localization and mapping (SLAM) to perform traversability analysis".
The paper, published in November 2016, is titled "Expanding the Detection of Traversable Area with RealSense for the Visually Impaired".
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5134613/
You can find information about using SLAM with ROS Kinetic by googling for 'os kinetic slam'. If your project can use OpenCV, ORB-SLAM2 is also a highly recommendable choice of SLAM system.
GitHub - raulmur/ORB_SLAM2: Real-Time SLAM for Monocular, Stereo and RGB-D Cameras, with Loop Detection and Relocalizati…
仔细考虑选项后，适合您的项目 - 听起来像地面上的移动机器人 - 可能是使用称为SLAM的机器人导航技术。
以下是参考SLAM的论文的引用：“在某些方法中，可导航地面检测的问题与定位任务一起解决.Perez-Yus使用RANSAC算法在人造室内场景中分割平面，等待密集的3D点
云”。
“这种方法不仅可以提取地面，还可以提升或下降楼梯，并通过视觉测距来确定用户的位置和方向.Lee还结合了视觉测距和基于特征的metri-拓扑同时定位和制图（SLAM）
）进行可穿越性分析“。
该论文发表于2016年11月，题目是“扩大对视觉障碍者的RealSense可穿越区域的检测”。
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5134613/
你可以通过谷歌搜索'os kinetic slam'找到有关使用SLAM和ROS Kinetic的信息。
如果您的项目可以使用OpenCV，ORB-SLAM2也是SLAM系统的一个非常值得推荐的选择。
GitHub - raulmur / ORB_SLAM2：用于单目，立体和RGB-D相机的实时SLAM，具有环路检测和重新定位...
以上来自于谷歌翻译
以下为原文
Having carefully considered the options, a good fit for your project - which sounds like a moving robot on the ground - may be to use the robotics navigation technique called SLAM.
Here is a quote from a paper that references SLAM: "In some approaches, the problem of navigable ground detection is addressed in conjunction with localization tasks. Perez-Yus used the RANSAC algorithm to segment planes in human-made indoor scenarios pending dense 3D point clouds".
"The approach is able to extract not only the ground but also ascending or descending stairs, and to determine the position and orientation of the user with visual odometry. Lee also incorporated visual odometry and feature-based metri-topological simultaneous localization and mapping (SLAM) to perform traversability analysis".
The paper, published in November 2016, is titled "Expanding the Detection of Traversable Area with RealSense for the Visually Impaired".
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5134613/
You can find information about using SLAM with ROS Kinetic by googling for 'os kinetic slam'. If your project can use OpenCV, ORB-SLAM2 is also a highly recommendable choice of SLAM system.
GitHub - raulmur/ORB_SLAM2: Real-Time SLAM for Monocular, Stereo and RGB-D Cameras, with Loop Detection and Relocalizati…
举报
举报
