Embedded Motion Control 2014 Group 7

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Group members

Name Email
Maurice van de Ven m dot l dot j dot v dot d dot ven @ student dot tue dot nl
Pim Duijsens p dot j dot h dot duijsens @ student dot tue dot nl
Glenn Roumen g dot h dot j dot roumen @ student dot tue dot nl
Wesley Peijnenburg w dot peijnenburg @ student dot tue dot nl
Roel Offermans r dot r dot offermans @ student dot tue dot nl

Planning

WeekDeadlineGeneral planGroupmemberSpecific task
416-05-2014Complete Corridor Challenge
- - - - -- - - - -- - - - -- - - - -- - - - -
519-05-2014Research Maze Strategies and define modules
19-05-2014 before 10:45 h.RoelResearch possibilities for wall and corner detection with OpenCV
19-05-2014 before 10:45 h.GlennResearch possibilities for wall and corner detection with OpenCV
19-05-2014 before 10:45 h.WesleyResearch possibilities for arrow detection with OpenCV
19-05-2014 before 10:45 h.MauriceResearch possibilities for path planning and path tracker/driver
19-05-2014 before 10:45 h.PimResearch possibilities for path planning and path tracker/driver
- - - - -- - - - -- - - - -- - - - -- - - - -
626-05-2014Research functionality of ROS Packages: Gmapping and move_base
28-05-2014Decide: use of packages or write complete new code
30-05-2014Conceptual version of all modules are finished
- - - - -- - - - -- - - - -- - - - -- - - - -
706-06-2014Integration of the modules
- - - - -- - - - -- - - - -- - - - -- - - - -
813-06-2014Final presentation of the Maze Strategy
- - - - -- - - - -- - - - -- - - - -- - - - -
920-06-2014Maze Competition

Progress

Name Week 3 Week 4 Week 5 Week 6
Maurice van de Ven All tutorials, not all C++
Pim Duijsens All tutorials, but not all C++
Glenn Roumen All tutorials
Wesley Peijnenburg Tutorial #7
Roel Offermans All tutorials, not all C++


Time Table

Overview of time spent per group member
Lectures Group meetings Mastering ROS and C++ Preparing midterm assignment Preparing final assignment Wiki progress report Other activities
Week 1
Pim 2
Roel 2
Maurice 2
Wesley 2
Glenn 2
Week 2
Pim 2 2 4 3
Roel 0 2 10 6
Maurice 2 2 6 3
Wesley 2 2 4 2
Glenn 2 2 5 2
Week 3
Pim 2 1 12 2
Roel 2 4 10 2
Maurice 3 10 4
Wesley 2 3 10 1
Glenn 2 2 13 4
Week 4
Pim 2 5 1 7 3
Roel 2 5
Maurice 5 15
Wesley 2 5 9 1
Glenn 2 5 6 1
Week 5
Pim 2 2.5 7 0.5
Roel
Maurice 2 2.5 8
Wesley 2 5 7 3
Glenn 2 2.5 7
Week 6
Pim
Roel
Maurice
Wesley
Glenn

Different nodes and flow chart

Scheme nodes.png

Strategy for the Corridor Challenge

Emc07 2014 pro cor step1.png Emc07 2014 pro cor step2.png Emc07 2014 pro cor step3.png Emc07 2014 pro cor step4.png


Emc07 2014 pro cor step5.png Emc07 2014 pro cor step6.png Emc07 2014 pro cor step7.png Emc07 2014 pro cor step8.png

GMapping / SLAM

GMapping is being investigated as SLAM algorithm.

In order to run GMapping correctly a launch file gmap.launch is setup which initializes the correct settings.

As navigation stack move_base is used. An global overview of the move_base stack is given in the figure below.

Overview tf movebase.png

To launch the move_base stack, again a launch file is created which will initialize the correct settings. In global the move_base.launch file consist of the following files, each containing parameters for a specific task.

gmap.launch

costmap_common_params.yaml
global_costmap_params.yaml
local_costmap_params.yaml

base_local_planner_params.yaml

remap /cmd _vel -> pico/cmd_vel

While gmapping and move_base are running a tf tree can be made to see how the different nodes are linked. Viewing a tf tree can be done by:

$ rosrun tf view_frames

For correct settings of gmapping and move_base this results in:

Tftree movebase.png

Runnig Gmapping and move_base for simulations:

1. Start Gazebo:

$ gazebo 

2. Using another terminal, spawn the maze:

$ rosrun gazebo_map_spawner spawn_maze 

3. Launch PICO:

$ roslaunch pico_gazebo pico.launch 

4. Start RViz to visualize how PICO perceives the world through its sensors.

$ rosrun pico_visualization rviz 

5. Launch the gmapping plugin for PICO

$ roslaunch pico_2ndnav gmap.launch 

6. Launch the move_base package for PICO to navigate through the maze with the preferred settings.

$ roslaunch pico_2ndnav move_base.launch 


Remarks In local_costmap_params.yaml static_map should be false. (As a local costmap should not be static, it moves with the robot)

In costmap_common_params.yaml inflation_radius should probably be smaller than 0.55, the robot has a much smaller radius (in safe_drive we used 0.25 if i remember correctly?)

In pico_configuration.launch We should look very closely to the pkg and type that are used (for example, shouldn't the types end with .msg). Furthermore, it seems like it wants to run the messages as an executable, this is probably not our intention).

OpenCV - Arrow recognition

The OpenCV C++ files can be compiled using one of the given commands below. For the g++ command, the packages need to be specified manually.

$ g++ demo_opencv.cpp `pkg-config opencv --cflags --libs` -o demo_opencv 

Or you can make have ROS find the libaries for you:

$ rosmake demo_opencv 

Executing the program:

$ ./demo_opencv <argcount> <arg(s)> 


Troubleshooting:

There have been problems with the OpenCV and Highgui libraries (static libraries). This problem can be solved by replacing the following code:

// #include "cv.h" // (commented out)
#include "opencv2/opencv.hpp"
// #include <highgui.h> // (commented out)
#include <opencv/highgui.h>

The program might not always respond to input, this is can be due to a subscription to the wrong topic. Make sure you are streaming the images and check the ros-topic with:

  rostopic list  

Then the output gives "/pico/camera", "/pico/asusxtion/rgb/image_color", or a different name. Replace the referece in the following line of code:

  ros::Subscriber cam_img_sub = nh.subscribe("/pico/asusxtion/rgb/image_color", 1, &imageCallback); 


Runnig OpenCV on an image stream from a bag file:

In three separate terminals:

roscore
rosbag play <location of bag file>
./demo_opencv


Arrow recognition strategy:

The image is cropped using:

cv::Rect myROI(120,220,400,200);  // Rect_(x,y,width,height)
cv::Mat croppedRef(img_rgb, myROI); // The window is 480 rows and 640 cols