Embedded Motion Control 2013 Group 9: Difference between revisions
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=== Assignment === | === Assignment === | ||
The goal of the assignment is to get the real-time concepts in embedded software design operational. | |||
The concrete task that has to be solved is to let the PICO robot find his way out of a maze. The final demonstration by each participating group of 4-5 students will be performed during a contest, the winner of which is the group that exits the maze in the shortest amount of time. To prepare for this competition the following guidelines have to be considered: | |||
*to test with PICO and to prepare for the final contest, a simulator will be made available that mimics the in and outputs to the real robot. Specifics of this simulator will be presented in the first lecture on September 4th | |||
*the maze of the final competition will be constructed just before the competition. The maze presented in the simulator is therefore different from the real one used in the final contest. | |||
* both on the real and simulated PICO robot, three sources of sensor information will be available to perceive the environment and to derive the state of the robot: | |||
- laserdata provided by the forward pointing laser scanner, | |||
- images captured by the monocular camera, | |||
- odometry provided by the base controller | |||
* the robot can be actuated by sending information to the base controller | |||
* during the final contest, it is highly imperative that the PICO robot refrains from colliding with the walls in the maze. Colliding with the walls will result in severe time-penalties. | |||
=== Some theory about solving mazes === | === Some theory about solving mazes === | ||
Revision as of 12:58, 13 October 2013
Group members
| Name: | Student id: | Email: |
| Jeroen Lamers | 0771264 | j.w.lamers@student.tue.nl |
| Rens Samplonius | 0785119 | r.j.samplonius@student.tue.nl |
| Haico Ploegmakers | 0775395 | h.e.c.w.ploegmakers@student.tue.nl |
| Frank Evers | 0789890 | f.evers@student.tue.nl |
| Filipe Catarino | 0821789 | f.freire.catarino@student.tue.nl |
| Tutor: |
| Janno Lunenburg |
Planning
| Week: | Activities: | People: |
| Week 1 |
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* Everbody |
| Week 2 |
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| Week 3 |
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| Week 4 |
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| Week 5 |
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| Week 6 |
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| Week 7 |
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| Week 8 |
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Progress
Week 1: September 2 - September 8
The first week mainly consisted of installing the Ubuntu OS with all the required ROS/Gazebo software. This did not went smoothly as there is no easy available Ubuntu installation for Mac (1 member) and missing one tiny step in the Tutorials could end up with a not working environment.
It was decided that everyone should do all the tutorials to know how everything works, and that we would work with the software provided by the course material (QT for c++ and fuerte Ros).
Week 2: September 9 - September 15
During the second week everyone finished the tutorials for ROS and c++.
Robot Sensors
Researching the given example with the simulation environment shows that the laser data is acquired by scanning in a 270 degree angle with increments of 0.25 degrees. This information is saved in a a vector and can be used to obtain distances for every angle at a certain time.
Week 3: September 16 - September 22
The third week consisted of 2 parts:
- Creating the architecture of the system, by dividing all the necessary steps into functions.
- Focus on the corridor competition
System functions & Architecture
The group was split into two teams where 2 people where focusing on the architecture of the system. By doing this early it is clear how the system is going to be created. There is one main file that is able to call for all different functions that are required for the situation at hand. The focus of course is on the basic functions of the system for the corridor competition. These functions are:
- Driving in a straight line in the middle of the corridor
- Detecting the corner on either the left or the right side
- Turn into the corner and leave the corridor
- Stop outside the corridor
Corridor Competition concept
Because the contest dictates that the robot will be between the walls, and facing the end of the competition, the idea is that the robot is able to drive forward into the corridor. Because the robot is put there by human hand, and walls might not be exactly parallel there has to be some kind of control. By measuring the closest distance to the walls with the laser, the robot is able to calculate where the middle of the corridor is. The laser is then also used to calculate the angle between the robot and the wall.
The concept program for the corridor competition is drawn in the following schematic:
To make this program possible, the system has a main loop with a case switch. This will activate the functions that are required at that moment. When for example the corner is detected it will switch to that function.
Driving Straight: To drive straight the robot measures the closest distance to each wall and also the corresponding angle. Using this information the orientation of the robot and the position in the corridor is determined. Using a controller, the robot will drive forward and correct its position until it is moving forward in the middle of the corridor.
Corner Detection: The corner is detected by looking at an angle of 90 degrees. If there is a sudden change in that distance (opening in the wall) the system will switch to the corner function.
Turn into Corner: After detecting the corner, it will drive while keeping the corner at the same distance. After this it will drive straight until the walls disappear and stop.
Week 4: September 23 - September 29
Test on the Robot
After we created a program for the Corridor Competition, the simulation showed good results. By running the program with the robot in various positions in the Corridor we concluded that the program was functioning properly. After that came the testing on the Robot. There were a lot of problems with the Robot. For that reason we were not able to have normal testing until one day before the contest.
In the end the tests on the robot were successful. The Robot was able to drive straight trough the corridor, however due to the hysteresis, friction and the low values on the controller it drove in a stretched S-shape, like a snake. The corner however was very smooth.
The Competition
After some problems where the robot would turn after initialization, the competition was a success in the second try. Group 9 set the third time of 4 groups what were able to finish the competition.
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Strategy
After the competition and a brainstorm session we came to the conclusion that this method is only effective for straight corridors with single exits. Watching the maze that is provided with the simulation is is clear that there are a lot of different types of situations. Also decisions on where to at certain junctions is not supported by the current code. Therefor the strategy should contain 'mapping'. This way there is a way to detect the path in front of the robot while also saving everthing that was discovered before. This should prevent driving into allready explored parts.
Week 5: September 30 - October 6
This week we started with a totally new design for the pico software architecture. For the corridor competition we only focused on a particular task, driving straight and take one corner. In the real maze more functions and software features will be required. We started by separating the existing code in even more individual functions. We split our group in 3 subgroups
- Frank and Filipe look into analyzing of the laser data and come up with a matrix of “edges” from which lines can be determined.
- Rens and Jeroen will use this information to determine a trajectory through the junctions based on “nodes”.
- Haico wil look into the arrow detection with the camera.
Finding 'Hard Points'
The way to find corners is based on scanning the entire range of the laser. From the position of the robot, a corner can be detected by finding a sudden change in the distance in another direction. Using this theory, there are 2 types of corners: one where the middle is closest and the distance grows from this point (a corner to turn around), and also a corner that is opposed to this (a corner to turn before). This way the robot and drive to a junction, determine the type, and then use this information to take the specific corner.
Determine Trajectory in Junctions
After the 'hard points' are known, the junction can be determined. This way we have the possibility to pick one of the directions and also drive trough it. Because there are only so many possible junctions, it is possible to prepare for all of these and determine the trajectory.
Vision
Haico looked for a solution.
Week 6: October 7 - October 13
PICO
Assignment
The goal of the assignment is to get the real-time concepts in embedded software design operational.
The concrete task that has to be solved is to let the PICO robot find his way out of a maze. The final demonstration by each participating group of 4-5 students will be performed during a contest, the winner of which is the group that exits the maze in the shortest amount of time. To prepare for this competition the following guidelines have to be considered:
- to test with PICO and to prepare for the final contest, a simulator will be made available that mimics the in and outputs to the real robot. Specifics of this simulator will be presented in the first lecture on September 4th
- the maze of the final competition will be constructed just before the competition. The maze presented in the simulator is therefore different from the real one used in the final contest.
- both on the real and simulated PICO robot, three sources of sensor information will be available to perceive the environment and to derive the state of the robot:
- laserdata provided by the forward pointing laser scanner,
- images captured by the monocular camera,
- odometry provided by the base controller
- the robot can be actuated by sending information to the base controller
- during the final contest, it is highly imperative that the PICO robot refrains from colliding with the walls in the maze. Colliding with the walls will result in severe time-penalties.
Some theory about solving mazes
We start with obtaining some general and basic methods of solving a maze. With these methods in mind we can perhaps determine a good solution for the maze competition in the embedded motion course.
- Follow the wall
The name already explains what this methods does, it follows a wall. It is not very difficult to program this for the pico robot. At the initial point of the maze the robot just choses either the left or right wall and will follow this wall till it find an exit or when there is no exit it will return to the starting point. For the situation where the left wall has been chosen, when the robot is at a junction it always prefers to turn left or when this is not possible it goes straight ahead. There is no need to keep track of the junctions it took in the image below we depicted an example of this method.
In the image above we followed the left wall and as can be observed this is not the most efficient method however it will find an exit.
- Tremaux's algorithm
- Shortest path algorithm
Usefull website for more information: http://en.wikipedia.org/wiki/Maze_solving_algorithm
Software architecture
- ROS nodes
- C++ layout
- Main program flow
Laser data interpretation and processing
- Data preprocessing
Line and edge detection using Hough algorithm
TODO
Junction detection
TODO
Maze solve algorithm
TODO
Pico movement / driving
- Moving staight
- Turning left or right
- Crossing a cross
- Dead end
Arrow detection
TODO