On this demo, it is a Xtion Live Pro, which is powered by USB for convenience. For a Kinect v1, we could cut the wire and plug into a 12V dc output directly on the board of the robot.

We keep the map downsampled for rendering performance. Maybe with new GPUs, we could keep the map more dense while keeping smooth visualization. We can see at the end of the video, the rendering frame rate is already lower than at the beginning.

matlabbe ah alright.

Point clouds are very memory intensive! I am doing a similar type of pointcloud mapping on Android, using ARCore. One of the first things I noticed is how hard it is to keep that many points. If I compute points for an entire camera frame, and try to keep them, the device would run out of memory after about 30 seconds. Luckily all I need really is a birds eye view perspective, so I project the points to a 2D image and that works fine.

The robot is tele-operated using a gamepad. The best way to communicate the data you have to rtabmap is to use ROS and publish the right topics. See this example wiki.ros.org/rtabmap_ros/Tutorials/SetupOnYourRobot#Kinect_.2B-_Odometry_.2B-_2D_laser for more info!

I understood. I have 3dm-gx1 ımu. I want to get odometry messages with IMU instead of encoders. But as far as I know, linear velocity data to x and y axis is not obtained with IMU.How can ı measure odometry values with IMU.?

It is possible (integrating two times the acceleration), but it will have a lot of drift. You said you have a laser scanner, you can use it to get x,y parameters, or estimate odometry only with the laser scanner (like hector mapping). Here is another setup here: wiki.ros.org/rtabmap_ros/Tutorials/SetupOnYourRobot#Kinect_.2B-_2D_laser

Anton Myagotin The map's graph is filtered to keep around 1 node/meter, then a point cloud is created from each filtered node. In the visualization above, some clouds are effectively superposed.

+余煒森 Objects are found using RGB images. Visual features (SURF) are extracted from images of the books, then they are compared to the live RGB stream to find the same visual features.

kapil yadav It is a mini ITX with an i7 + SSD (no GPU). It is running Ubuntu 12.04 + ROS Hydro.

D435i is integrated in RTAB-Map standalone application (for hand-held mapping). It can be also used like the kinect above with rtabmap_ros package. Note that any RGB-D cameras and stereo cameras can be used with rtabmap_ros right know, if they comply with the standard ros interface for images.

In this demo, SLAM is done with lidar and rgb-d camera from "rtabmap_ros" package and books are detected using "find_object_2d" package. There is no face detection or object following here. cheers!

@@matlabbe what if we combine with object detection using camera?

The current documentation is on ros.org: wiki.ros.org/rtabmap_ros/Tutorials, when you have specific questions, you can ask them on ROS answers (answers.ros.org/questions/) or for on RTAB-Map's forum (official-rtab-map-forum.67519.x6.nabble.com/)

It is not required, but increase the precision of the mapping. In this video: ukposts.info/have/v-deo/l6GagHeOp21y0oU.html , only the Kinect is used.

On this demo: URG-04LX, Xtion Pro Live and wheel odometry from the robot.

Go to:- en.savefrom.net/1-how-to-download-youtube-video/ Then paste the url of any youtube video (in your case this video's url) in the box.

a (2009 if I remember) Intel NUC is on the robot, the drive motors use custom boards