Using TUM benchmark datasets for rgbd slam evaluation [closed]

asked 2013-03-20 01:52:22 -0500

sai gravatar image

updated 2014-01-28 17:15:48 -0500

ngrennan gravatar image

I want to use TUM kinect datasets with ground truths which were published which can be found here.

I have a visual odometry code (using ICP) which needs both depth image and pointcloud, and found that the published datasets dont have them packed into one file. I found a script file which adds pointclouds to ROSBAG file.

  1. Should I save the script file in .sh format or .py format ?
  2. When I run it in terminal, I am getting an error as below. I have cv_bridge in the ROS_PACKAGE_PATH because roscd cv_bridge takes me to its location

./ rgbd_dataset_freiburg1_desk2.bag Traceback (most recent call last): File "./", line 32, in <module> from cv_bridge import CvBridge, CvBridgeError ImportError: No module named cv_bridge

3.The visual odometry code gives the position and orientation taking the first pose as origin, but the datasets have some offset. So How can this be adjusted ?

4.The axes of the frames which the datasets publish and the output which i get from visual odometry code may not be aligned, so how can this be adjusted?

The visual odometry code which I have basically gives an output as tf(estimated from ICP).

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Closed for the following reason question is not relevant or outdated by tfoote
close date 2015-11-26 03:03:59.351363