Embedded Motion Control 2013 Group 3

Contact info

Vissers, Yorrick	0619897	y.vissers@student.tue.nl
Wanders, Matthijs	0620608	m.wanders@student.tue.nl
Gruntjens, Koen	0760934	k.g.j.gruntjens@student.tue.nl
Bouazzaoui, Hicham	0831797	h.e.bouazzaoui@student.tue.nl
Zhu ,Yifan	0828010	y.zhu@student.tue.nl

Meeting hours

Mondays 11:00 --> 17:00
Wednesdays 8:45 --> 10:30

Meet with tutor: Mondays at 14:00

Planning

Ma 09 sept:

• Finish installation of everything
• Go through ROS (beginner) and C++ manual

Wo 11 sept:

• Finish ROS, C++ manuals
• Start thinking about function architecture

Ma 16 sept:

• Design architecture
• Functionality division
• Divide programming tasks

Do 19 sept:

• Finish "initialize" (Koen, Hicham, Yifan)
• Finish "drive_parallel" (Matthijs, Yorrick)
• Testing with robot at 13:00-14:00

Wo 25 sept:

• Finish clean_rotation
• Finish gap_handling
• Putting things together
• Corridor Challenge

PICO usefull info

• minimal angle = 2,35739
• maximal angle = -2,35739
• angle increment = 0,00436554
• scan.range.size() = 1081

Strategy

We will use one node that "spins" and subscribes to the sensordata, and publishes the velocities.

The main controller can be in six states:

• state_initialize: return initial setpoint??
• state_drive_parallel: Keep the robot at a fixed distance (setpoint) from the right wall while driving.
• state_gap_handling: When arriving at the center of a gap (to the right). Rotate in place untill parallel with new right wall.
• state_stop: Stops the robot when necessary.
• state_finalize: When no longer between two walls and no maze in front, abort.
• state_turn_around: when at a dead end, turn around.

Design approach & conventions

• datastructures.h: put all global variables and datastructures here.
• states: each contains the functionality of a state.
• conditions: each checks a certain condition to determine the next state.

• theseus is name of the package/node to execute
• theseus_controller is the controller that is iterated and runs:

   Gather conditions e.g.: crash_avoidance, gap_detection.
   Based on the information a state will be chosen and executed.
   At the end of the state, the velocities will be published.