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. http://vision.in.tum.de/data/datasets/rgbd-dataset/download

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 add_pointclouds_to_bagfile.py 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

./add_pointclouds_to_bagfiles.sh rgbd_dataset_freiburg1_desk2.bag Traceback (most recent call last): File "./add_pointclouds_to_bagfiles.sh", 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).

edit retag flag offensive reopen merge delete

Closed for the following reason question is not relevant or outdated by tfoote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