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  1. Yes
  2. Yes
  3. Yes
  4. Yes
  5. Depends on your environment, I think 75deg. will work fine. We haven't tested the algorithm using webcams, we're using PointGrey Bumblebee2 stereo cameras. The authors of the libviso2 core library use this custom setup: http://www.cvlibs.net/datasets/kitti/setup.php
  6. On your screenshot it looks like the tf from base_link to left_camera is setup correctly. Try to reset the odometer (call the stereo_odometer/reset_pose service). This should set the odom->base_link tf to zero. From the camera image seen in your screenshot I would recommend pointing the camera slightly upwards as the floor does not have many features and the reflections might confuse the algorithm. Of course you'll have to introduce that physical change in your base_link->left_camera static transform.

I recommend to check out also our wrapper for fovis: http://www.ros.org/wiki/fovis_ros

Please note that visual odometers have major limitations. If there are not enough features in the scene or the images are not well synchronized or the image is blurry or the baseline is to short for the depth of the scene or ... it will not work well. It is always better to fuse it with an IMU and/or wheel odometry.