CS 378 - Autonomous Vehicles in Traffic I Week 8b - Transformations - - PowerPoint PPT Presentation

CS 378 - Autonomous Vehicles in Traffic I

Week 8b - Transformations

Announcements

• I did not go through the 3 single person projects that I were
• n the slides on Monday
• Any thoughts about groups or projects yet?

○ Please send emails to me if you have any questions

• The rviz problems on the CS machines should now be

resolved.

• If rviz crashes out unexpectedly or seg faults, remove ~/.

rviz/*

• There seems to be a problem with rosmake art_run on non

Oneiric systems. Run it without the --rosdep-install flag for now.

Transformations

• Transformations have typically played an important role in

robotics and some computer vision applications

• Important for the idea of sensor registration
• Can be useful for verifying and understanding sensor

readings.

Example 1 - Multiple Kinects

[http://www.youtube.com/watch?v=5-w7UXCAUJE]

Example 2 - Line Detection (RoboCup)

Input from Camera Detection How can we get rid of these spurious readings?

Example 2 (contd)

How do we perform this projection?

• Proprioception gives us estimates of all the joints
• Assuming that the contact foot is on the ground - we can

calculate the position and orientation of the camera w.r.t. to the ground.

The tf tree - PR2

[Image taken from http://www.ros.org/wiki/tf]

PR2 Robot

Different coordinate represent either joints or other significant points of interest on the robot body. You have to define a given joint relative to some other joint or reference point. For instance, the elbow joint will be described relative to the shoulder joint.

The tf tree - Marvin

The tf tree - Marvin

• How is this useful to us?
• The tf tree defines the relations between various sensors.
• Say if we want to fill point cloud data with color?

○ Terminal 1 ■ roscore ○ Terminal 2 ■ rosparam set /use_sim_time true ■ rosbag play --clock <bag-file> ○ Terminal 3 ■ rosrun velodyne_pointcloud cloud_node ■ (Remember to remap topics for older bag files) ○ Terminal 4 ■ rosmake rgb_pointcloud ■ rosrun rgb_pointcloud rgb_pointcloud_publisher _image_transport:=compressed

Future Ideas

• Change the tf tree
• (Automated Surveying) Figure out the correct position of

the SICK Lidars

• (Automated Surveying) Automated registration of cameras

wrt to velodyne

• (Velodyne Calibration) Incorporate pitch and roll

determined through the calibration tool into the tf tree.

Onwards then!

How to use the tf code?

• Go through the tf tutorials!
• http://www.ros.org/wiki/tf/Tutorials
• Even if you are not implementing tf - I recommend

everyone complete the introduction to tf tutorial

○ http://www.ros.org/wiki/tf/Tutorials/Introduction%20to%20tf

What does tf provide?

• tf maintains the relationship between coordinate frames in

a tree structure buffered in time [http://www.ros.org/wiki/tf]

• It provides functions to transform points, vectors etc. from a

coordinate frame to another.

• pcl_tf provides methods for transforming pcl data

structures (yay!)

Some basic tf tools

• Viewing the tf tree

○ rosrun tf view_frames ○ evince frames.pdf

• Viewing a particular transformation

○ rosrun tf tf_echo <source_frame> <target_frame> ○ rosrun tf tf_echo /vehicle /velodyne

• Publishing a static transform

○ rosrun tf static_transform_publisher x y z yaw pitch roll frame_id child_frame_id period_in_ms ○ rosrun tf static_transform_publisher 5 0 0 0 0 0 /some_ref /vehicle 100

• All of these are explained with an example in the introduction to tf

tutorial.

Output of view_frames - Marvin

Using tf in code

• Publishing tf information

○ A simple example of publishing tf messages is art_common/src/vehicle_static_tf.cc ○ In this file we publish the same tf tree I showed earlier

• Keep in mind that there are 2 different conventions:

○ Regular Frame: +x is forward, +y is left, +z is up ○ Optical Frame: +z is forward, +x is right, +y is down ○ Both of these are still following the right handed convention!

The code

The code

The code

Subscribing to tf

A simple example

• This is useful for transforming some simple data structures -
• r looking up the transformations themselves
• Check out the velodyne_pcl package to transform

pointclouds

tf, rviz and messages

• Each message containing sensor data should have a

frame_id corresponding to the tf frame it is in. ○ outMsg.header.frame_id = "some_frame_id"; ○ outMsg.header = inMsgPtr->header; ○ Some of you may be experiencing this problem in Assignment 3

• Let's play around with tf in rviz.

Programming Assignment 4 discussion

• Let's take a look at the camera output from the car