{"id":5952,"date":"2023-03-28T09:00:08","date_gmt":"2023-03-28T01:00:08","guid":{"rendered":"https:\/\/www.neuvition.cn\/?p=5952"},"modified":"2023-05-06T09:58:21","modified_gmt":"2023-05-06T01:58:21","slug":"%e6%bb%a4%e6%b3%a2%e7%ae%97%e6%b3%95","status":"publish","type":"post","link":"https:\/\/www.neuvition.cn\/technology-blog\/%e6%bb%a4%e6%b3%a2%e7%ae%97%e6%b3%95.html","title":{"rendered":"\u6ee4\u6ce2\u7b97\u6cd5"},"content":{"rendered":"\n<p>\u6ee4\u6ce2\u7b97\u6cd5\uff1a\u8fd9\u4e9b\u7b97\u6cd5\u7528\u4e8e\u4ece\u70b9\u4e91\u6570\u636e\u4e2d\u53bb\u9664\u6742\u70b9\u3001\u5f02\u5e38\u503c\u6216\u4e0d\u9700\u8981\u7684\u70b9\u3002<\/p>\n\n\n\n<p><strong>\u6fc0\u5149\u96f7\u8fbe\u70b9\u4e91\u6ee4\u6ce2\u7b97\u6cd5\u7684\u5e94\u7528<\/strong><\/p>\n\n\n\n<p>\u6fc0\u5149\u96f7\u8fbe\uff08Light Detection and Ranging\uff09\u70b9\u4e91\u6ee4\u6ce2\u7b97\u6cd5\u7528\u4e8e\u5904\u7406\u539f\u59cb\u6fc0\u5149\u96f7\u8fbe\u6570\u636e\u5e76\u53bb\u9664\u4e0d\u9700\u8981\u6216\u9519\u8bef\u7684\u70b9\uff0c\u4ec5\u7559\u4e0b\u51c6\u786e\u4ee3\u8868\u73af\u5883\u6216\u76ee\u6807\u7269\u4f53\u8868\u9762\u7684\u70b9\u3002 \u8fd9\u4e9b\u7b97\u6cd5\u5bf9\u4e8e\u8bb8\u591a\u5e94\u7528\u81f3\u5173\u91cd\u8981\uff0c\u5305\u62ec\u81ea\u52a8\u9a7e\u9a76\u6c7d\u8f66\u3001\u5730\u5f62\u6d4b\u7ed8\u3001\u57ce\u5e02\u89c4\u5212\u548c\u6797\u4e1a\u7ba1\u7406\u3002 \u901a\u8fc7\u4ece\u70b9\u4e91\u6570\u636e\u4e2d\u53bb\u9664\u566a\u70b9\u548c\u5f02\u5e38\u503c\uff0c\u6ee4\u6ce2\u7b97\u6cd5\u63d0\u9ad8\u4e86\u540e\u7eed\u5206\u6790\u7684\u51c6\u786e\u6027\u548c\u53ef\u9760\u6027\uff0c\u4f8b\u5982\u5bf9\u8c61\u68c0\u6d4b\u3001\u5730\u5f62\u5efa\u6a21\u548c\u5206\u7c7b\u3002 \u6839\u636e\u5177\u4f53\u5e94\u7528\u548c\u6fc0\u5149\u96f7\u8fbe\u4f20\u611f\u5668\u7279\u6027\uff0c\u4f7f\u7528\u4e0d\u540c\u7684\u6ee4\u6ce2\u6280\u672f\uff0c\u5305\u62ec\u57fa\u4e8e\u8ddd\u79bb\u3001\u57fa\u4e8e\u5f3a\u5ea6\u548c\u57fa\u4e8e\u51e0\u4f55\u7684\u65b9\u6cd5\u3002<\/p>\n\n\n\n<p><strong>\u4e0b\u9762\u5217\u51fa\u4e86\u5341\u79cd\u5e38\u7528\u7684\u6fc0\u5149\u96f7\u8fbe\u70b9\u4e91\u8fc7\u6ee4\u7b97\u6cd5\u53ca\u5176\u7b80\u8981\u8bf4\u660e\u548c\u4e0b\u8f7d\u5730\u5740\uff1a<\/strong><\/p>\n\n\n\n<p>1. Voxel Grid Filter\uff08\u4f53\u7d20\u7f51\u683c\u6ee4\u6ce2\u5668\uff09\uff1a\u6b64\u6ee4\u6ce2\u5668\u5c06\u70b9\u4e91\u79bb\u6563\u5316\u4e3a\u4f53\u7d20\uff0c\u5e76\u7528\u8d28\u5fc3\u66ff\u6362\u6bcf\u4e2a\u4f53\u7d20\u5185\u7684\u70b9\u3002 \u8fd9\u964d\u4f4e\u4e86\u70b9\u4e91\u7684\u5bc6\u5ea6\uff0c\u540c\u65f6\u4fdd\u7559\u4e86\u5176\u6574\u4f53\u7ed3\u6784\u3002 <\/p>\n\n\n\n<p>\u4e0b\u8f7d\u5730\u5740\uff1ahttps:\/\/github.com\/PointCloudLibrary\/pcl\/blob\/master\/filters\/include\/pcl\/filters\/voxel_grid.h<\/p>\n\n\n\n<p>2. Statistical Outlier Removal\uff08\u7edf\u8ba1\u5f02\u5e38\u503c\u79fb\u9664\uff09\uff1a\u8be5\u6ee4\u6ce2\u5668\u6839\u636e\u76f8\u90bb\u70b9\u7684\u7edf\u8ba1\u7279\u6027\u8bc6\u522b\u70b9\u4e91\u4e2d\u7684\u5f02\u5e38\u503c\u3002 \u5b83\u79fb\u9664\u4e0e\u76f8\u90bb\u70b9\u7684\u8ddd\u79bb\u8d85\u8fc7\u7279\u5b9a\u9608\u503c\u7684\u70b9\u3002 <\/p>\n\n\n\n<p>\u4e0b\u8f7d\u5730\u5740\uff1ahttps:\/\/github.com\/PointCloudLibrary\/pcl\/blob\/master\/filters\/include\/pcl\/filters\/statistical_outlier_removal.h<\/p>\n\n\n\n<p>3. Radius Outlier Removal\uff08\u534a\u5f84\u5f02\u5e38\u503c\u5220\u9664\uff09\uff1a\u6b64\u6ee4\u6ce2\u5668\u6839\u636e\u90bb\u8fd1\u70b9\u7684\u7edf\u8ba1\u5c5e\u6027\u8bc6\u522b\u70b9\u4e91\u4e2d\u7684\u5f02\u5e38\u503c\u3002\u5b83\u5220\u9664\u4e86\u4e0e\u90bb\u5c45\u4e4b\u95f4\u7684\u8ddd\u79bb\u8d85\u8fc7\u4e00\u5b9a\u9608\u503c\u7684\u70b9\u3002 <\/p>\n\n\n\n<p>\u4e0b\u8f7d\u5730\u5740\uff1ahttps:\/\/github.com\/PointCloudLibrary\/pcl\/blob\/master\/filters\/include\/pcl\/filters\/radius_outlier_removal.h<\/p>\n\n\n\n<p>4. Pass Through Filter\uff08\u76f4\u901a\u6ee4\u6ce2\u5668\uff09\uff1a\u6b64\u6ee4\u6ce2\u5668\u5220\u9664\u6cbf\u7740\u6307\u5b9a\u8f74\u7684\u7ed9\u5b9a\u503c\u8303\u56f4\u4e4b\u5916\u7684\u70b9\u3002 \u5b83\u53ef\u7528\u4e8e\u63d0\u53d6\u4f4d\u4e8e\u7279\u5b9a\u611f\u5174\u8da3\u533a\u57df\u5185\u7684\u70b9\u4e91\u5b50\u96c6\u3002 <\/p>\n\n\n\n<p>\u4e0b\u8f7d\u5730\u5740\uff1ahttps:\/\/github.com\/PointCloudLibrary\/pcl\/blob\/master\/filters\/include\/pcl\/filters\/passthrough.h<\/p>\n\n\n\n<p>5. Conditional Removal Filter\uff08\u6761\u4ef6\u6ee4\u6ce2\u5668\uff09\uff1a\u6b64\u6ee4\u6ce2\u5668\u5220\u9664\u4e86\u6ee1\u8db3\u7ed9\u5b9a\u5c5e\u6027\u6761\u4ef6\u96c6\u7684\u70b9\u3002\u5b83\u53ef\u7528\u4e8e\u63d0\u53d6\u7279\u5b9a\u7279\u5f81\u6216\u4ece\u70b9\u4e91\u4e2d\u53bb\u9664\u6742\u70b9\u3002 <\/p>\n\n\n\n<p>\u4e0b\u8f7d\u5730\u5740\uff1ahttps:\/\/github.com\/PointCloudLibrary\/pcl\/blob\/master\/filters\/include\/pcl\/filters\/conditional_removal.h<\/p>\n\n\n\n<p>6. Moving Least Squares Filter\uff08\u79fb\u52a8\u6700\u5c0f\u4e8c\u4e58\u6cd5\u6ee4\u6ce2\u5668\uff09\uff1a\u8be5\u6ee4\u6ce2\u5668\u4f7f\u7528\u52a0\u6743\u6700\u5c0f\u4e8c\u4e58\u7b97\u6cd5\u5c06\u5149\u6ed1\u8868\u9762\u62df\u5408\u5230\u70b9\u4e91\u3002 \u53ef\u7528\u4e8e\u70b9\u4e91\u53bb\u566a\uff0c\u63d0\u53d6\u6cd5\u7ebf\u3001\u66f2\u7387\u7b49\u7279\u5f81\u3002 <\/p>\n\n\n\n<p>\u4e0b\u8f7d\u5730\u5740\uff1ahttps:\/\/github.com\/PointCloudLibrary\/pcl\/blob\/master\/surface\/include\/pcl\/surface\/mls.h<\/p>\n\n\n\n<p>7. Normal Estimation\uff08\u6cd5\u5411\u8ba1\u7b97\uff09\uff1a\u8be5\u7b97\u6cd5\u901a\u8fc7\u5c06\u5e73\u9762\u62df\u5408\u5230\u76f8\u90bb\u70b9\u6765\u4f30\u8ba1\u70b9\u4e91\u7684\u8868\u9762\u6cd5\u7ebf\u3002 \u5b83\u53ef\u7528\u4e8e\u8ba1\u7b97\u66f2\u7387\u548c\u65b9\u5411\u7b49\u7279\u5f81\u3002<\/p>\n\n\n\n<p>\u4e0b\u8f7d\u5730\u5740\uff1ahttps:\/\/github.com\/PointCloudLibrary\/pcl\/blob\/master\/features\/include\/pcl\/features\/normal_3d.h<\/p>\n\n\n\n<p>8. Curvature Estimation\uff08\u66f2\u7387\u4f30\u8ba1\uff09\uff1a\u8be5\u7b97\u6cd5\u901a\u8fc7\u5c06\u4e8c\u6b21\u66f2\u9762\u62df\u5408\u5230\u76f8\u90bb\u70b9\u6765\u4f30\u8ba1\u70b9\u4e91\u8868\u9762\u7684\u66f2\u7387\u3002 \u5b83\u53ef\u7528\u4e8e\u68c0\u6d4b\u9510\u8fb9\u548c\u5176\u4ed6\u51e0\u4f55\u7279\u5f81\u3002 <\/p>\n\n\n\n<p>\u4e0b\u8f7d\u5730\u5740\uff1ahttps:\/\/github.com\/PointCloudLibrary\/pcl\/blob\/master\/features\/include\/pcl\/features\/curvature.h<\/p>\n\n\n\n<p>9. Euclidean Cluster Extraction\uff08\u6b27\u6c0f\u805a\u7c7b\u63d0\u53d6\uff09\uff1a\u8be5\u7b97\u6cd5\u6839\u636e\u6b27\u51e0\u91cc\u5fb7\u8ddd\u79bb\u5c06\u70b9\u4e91\u4e2d\u5f7c\u6b64\u9760\u8fd1\u7684\u70b9\u5206\u7ec4\u4e3a\u7fa4\u96c6\u3002 \u5b83\u53ef\u7528\u4e8e\u5c06\u70b9\u4e91\u5206\u5272\u6210\u4e0d\u540c\u7684\u5bf9\u8c61\u6216\u533a\u57df\u3002 <\/p>\n\n\n\n<p>\u4e0b\u8f7d\u5730\u5740\uff1ahttps:\/\/github.com\/PointCloudLibrary\/pcl\/blob\/master\/segmentation\/include\/pcl\/segmentation\/extract_clusters.h<\/p>\n\n\n\n<p>10. Smoothed Voxel Occupancy Filter\uff08\u5e73\u6ed1\u4f53\u7d20\u5360\u636e\u6ee4\u6ce2\u5668\uff09\uff1a\u6b64\u6ee4\u6ce2\u5668\u5bf9\u70b9\u4e91\u8fdb\u884c\u4f53\u7d20\u5316\u5904\u7406\uff0c\u5e76\u4f7f\u7528\u6838\u5bc6\u5ea6\u4f30\u8ba1\u6765\u4f30\u8ba1\u6bcf\u4e2a\u4f53\u7d20\u7684\u5360\u636e\u60c5\u51b5\u3002 \u5b83\u53ef\u7528\u4e8e\u751f\u6210\u73af\u5883\u7684 3D \u5360\u636e\u5730\u56fe\u3002 <\/p>\n\n\n\n<p>\u4e0b\u8f7d\u5730\u5740\uff1ahttps:\/\/github.com\/ethz-asl\/voxblox\/blob\/master\/voxblox_ros\/include\/voxblox_ros\/esdf_server.h<\/p>\n","protected":false},"excerpt":{"rendered":"<p>\u6ee4\u6ce2\u7b97\u6cd5\uff1a\u8fd9\u4e9b\u7b97\u6cd5\u7528\u4e8e\u4ece\u70b9\u4e91\u6570\u636e\u4e2d\u53bb\u9664\u6742\u70b9\u3001\u5f02\u5e38\u503c\u6216\u4e0d\u9700\u8981\u7684\u70b9\u3002<\/p>\n","protected":false},"author":4,"featured_media":5953,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":[],"categories":[489],"tags":[492],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v15.5 - 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