{"id":981,"date":"2022-01-20T07:00:40","date_gmt":"2022-01-20T07:00:40","guid":{"rendered":"https:\/\/webroad-seisaku.com\/fujiko-test\/?p=981"},"modified":"2023-08-07T01:18:54","modified_gmt":"2023-08-07T01:18:54","slug":"3d-lidar-slam-demo-without-external-gnss-pt2","status":"publish","type":"post","link":"https:\/\/webroad-seisaku.com\/fujiko-test\/archives\/981","title":{"rendered":"Kudan 3D-Lidar SLAM (KdLidar) new demo: Sharp point cloud with a Lidar without external GNSS nor IMU - Part 2"},"content":{"rendered":"

As we continue to enhance our Lidar SLAM capabilities without relying on external sensors, we took a Livox Avia, and put it through the test. Unlike the rotating 360 degree FOV Ouster OS1-64<\/a> from our previous demonstration, the Livox Avia<\/a> is a 70 degree directional Lidar with a built-in IMU, and we tested the Avia in a handheld configuration. The results were positively stunning.<\/p>\n

For tracking and creating point clouds with Lidar SLAM, the following 2 factors create the biggest challenges
\n\u2022\u2022\u2022 No external GNSS or IMU
\n\u2022\u2022\u2022 Limited field of view (FOV) - not 360 degrees<\/p>\n

We configured this demonstration with both conditions to see how well our Lidar SLAM performs in creating a crisp point cloud. As you can see from the video below, using only the Lidar and the internal IMU, the details are fantastic without any ghosting - even down to the individual powerlines.<\/p>\n

Given that the Livox Avia is one of the most affordable 3D-Lidars, paired with Kudan\u2019s Lidar SLAM, you won\u2019t need to make the trade-off between cost, point cloud quality, and still have a very cost-effective and efficient mapping tool to produce the crisp and accurate high-quality point clouds your projects demand.<\/p>\n

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As with our previous demo<\/a>, this demonstration highlights KdLidar\u2019s fundamental performance without any external sensors, and we can further fuse GNSS and external IMU, INS and other external references to increase the performance and quality of point clouds created from Lidar based scanners.<\/p>\n

Please see the demo here:<\/p>\n