Embedded Motion Control 2014 Group 5
Group 5
| Name | Student | |
| Paul Blatter | 0825425 | p dot blatter at student dot tue dot nl |
| Kevin van Doremalen | 0797642 | k dot p dot j dot v dot doremalen at student dot tue dot nl |
| Robin Franssen | 0760374 | r dot h dot m dot franssen at student dot tue dot nl |
| Geert van Kollenburg | 0825558 | g dot o dot m dot v dot kollenburg at student dot tue dot nl |
| Niek Wolma | 0 | n dot a dot wolma at student dot tue dot nl |
Planning
Week 1
- Instal Ubuntu
- Instal ROS
- Setup SVN
- Tutorials
Week 2
- Continu tutorials
- Setting up program for first test
Week 3
- Finishing tutorials
- Continu on program first test
- First test robot
- Program architecture
Week 4
- Everyone has finished the tutorials
- Working on program for the robot (we started too complex and therefore we have to build a more simple program for the corridor challenge)
- Setting up program for corridor challenge
- Second test robot (unfortunately, we didn't manage to test with the robot)
- Corridor challenge (PICO did the job with our program, which wasn't tested before! More information about the program can be found below.)
Week 5
- Meeting with tutor on Tuesday May 19th<
The following subjects will be discussed during the meeting:
- Evaluation corridor challenge
- Setting up a clear program structure (group)
- Implementation of odometry data (1 person)
- ROS structure (1 person)
- Improvement of program for corridor challenge for implementation in final challenge (1 person)
- Path planning (1 person)
- Detection of arrows with camera (1 person)
Week 6
Week 7
Week 8
Week 9
- Maze challenge
Introduction
The goal of this course is to implement (embedded) software design (with C++ and ROS) to let a humanoid robot navigate autonomously. The humanoid robot Pico is programmed to find its way through a maze, without user intervention.
This wiki page contains the approach and choices that were made by group 5.
Corridor Challenge
Program Architecture
Laser data
The robot contains a laser, which has a view of 270 degrees.
Odometry
Odometry is the use of data of the angular positions of the robot wheels. This data is used to estimate the position of the robot relative to a starting point. The angular positions are converted into Carthesian coordinates (x-, y- and theta-direction). This data is never fully accurate, inter alia due to wheel slip.