Context

As my research concentrates on the perception part of Robotics, my research is in the Informatics Institute part of the Computer Vision group.

Wishlist

• The HDPR has a SLAM approach based on Rao-Blackwellised Particle Filtering.
• The idea is to investigate if it is possible to sample particles in a 2D grid that has the same resolution as the local map and to fuse nearby cells for each cell of the map according to the variance of the robot's translation.
• First look at the dependencies:
  • ga-slam is based on the Robot Construction Kit Rock
  • Rock has several tutorials, including installing packages.
  • Rock-core is based on ROS and Orocos. There a several Orocos-ROS integration examples.
  • Both ROS and Orocos are dependent on PCL-library.
  • Tried the PCL-ROS tutorial Turning a PointCloud into an Image.
  • PCL has several Tutorials.
  • Look at PCL Walkthrough
    • The Filtering tutorial
    • The Features tutorial
    • The Keypoints tutorial (interacts with KdTree and Octree)
    • The Registration tutorial
    • The KdTree tutorial
    • The Octree tutorial
    • The Segmentation tutorial
    • The Sample consensus tutorial
    • The Surface tutorial
    • The Range image tutorial
    • The Visualisation tutorial
    • The I/O tutorial (partly done). Consist of more than 4 tutorials:
      • The PCD (Point Cloud Data) file format tutorial (finished)
      • Reading PointCloud data from PCD files tutorial (finished)
      • Writing PointCloud data to PCD files tutorial (skipped)
      • Concatenate the points of two Point Clouds tutorial (skipped)
      • The OpenNI Grabber Framework in PCL tutorial (simple-viewer was working with the Asus Xtion Pro on March 15)
      • Grabbing point clouds from DepthSense cameras tutorial (realsense-viewer worked with the Intel RealSense DS435 on at March 24, not clear if pcl-library is made with WITH_DSSDK enabled. On March 10 I had the in-hand scanner example working with the Intel RealSense DS435)