Embedded Motion Control 2015 Group 6: Difference between revisions

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:*'''Task Control Feedforward:''' Contributes in the implementation of control actions on the robot depending on the state and the goal of the challenge.
:*'''Task Control Feedforward:''' Contributes in the implementation of control actions on the robot depending on the state and the goal of the challenge.


'''Environmental Context:''' Semantic maze model.
2) '''Environmental Context:''' Semantic maze model.


2) '''Challenge Context:''' All information regarding the rules  and the goals of the  ''“A-Maze-ing challenge”''  are stored in this context.
3) '''Challenge Context:''' All information regarding the rules  and the goals of the  ''“A-Maze-ing challenge”''  are stored in this context.


3) '''Robot Context:''' This incorporates the low level specifications of the PICO robot.  
4) '''Robot Context:''' This incorporates the low level specifications of the PICO robot.  


4) '''Skills Context:''' Contains the above mentioned robot functionalities.
5) '''Skills Context:''' Contains the above mentioned robot functionalities.


== Interfaces ==
== Interfaces ==

Revision as of 20:10, 5 May 2015

Group Members

Name: Student id: E-mail:
Akash Agarwal 0923269 a.agarwal@student.tue.nl
Angus Pere 0926353 a.f.pere@student.tue.nl
Ashish Yadav 0925559 a.yadav@student.tue.nl
Floris Remmen 0920072 f.remmen@student.tue.nl
S. Cagil Mayda 0926975 s.c.mayda@student.tue.nl
Ugonna Mbaekube 0927006 u.o.mbaekube@student.tue.nl
René van de Molengraft Tutor m.j.g.v.d.molengraft@tue.nl

 

Planning

Week 1: 22 April - 29 April

  • Introduction lecture
  • Meeting 1: Initial design document & C++ tutorials
  • Ubuntu and other required softwares Installation

Week 2: 29 April - 6 May

  • 27-04 12:00: Deadline initial design
  • Finishing C++ tutorials
  • Start studyin maze algorithms
  • Meeting 2: Division of team roles in the project
  • Reading tutorials
  • Prepare presentation

Week 3: 4 May - 10 May

  • 6 May: First presentation of the design

Week 4: 11 May - 17 May

  • 13 May: Corridor competition

Week 5: 18 May - 24 May

  • Lecture 3: Composition Pattern part II by Herman Bruyninckx

Week 6: 25 May - 31 May

  • 27 May: Second presentation of the design

Week 7: 1 June - 7 June

  • Lecture 4: Communication patterns

Week 8: 8 June - 14 June

  • 10 June: Presentation of final design

Week 9: 15 June - 21 June

  • 17 June: Final competition

Initial Deisgn

Goal

The goal of the “A-Maze-ing challenge” is to design and implement a software for the PICO robot to navigate through a maze autonomously while optimizing time.

Requirements

  • To program a PICO robot to participate in the “A-Maze-ing challenge”.
  • The PICO robot should be able to navigate through the maze autonomously.
  • The PICO robot should be able to navigate through any maze regardless of its configuration.
  • The PICO robot should be able to avoid all obstacles during its navigation through the maze including contact with the walls of the maze.
  • The PICO robot should never get “stuck” at any position in the maze.
  • The PICO robot should be able to make use of its sensors to navigate the maze.
  • The PICO robot should have some sort of “memory” that prevents it from moving back towards paths already navigated through.
  • The PICO robot should be able to find the optimal path through the maze while optimizing time.
  • After navigating through the maze, the PICO robot should be able to autonomously terminate its movement.

Functions

The basic functionality of the robot are as follows:

1) Motion

  • Move Forward
  • Move Backwards (Reverse)
  • Turn Left/Turn Right


2) Environmental Awareness

  • Obstacle Detection using sensors
  • Decision making during navigation
  • Termination of movement on completion of the maze
  • “Memory” storage
  • Optimal Path calculation
  • Localisation

Components and Specificications

Schematic overview of the components to be used in the software design

Components.png

1) Task Context: Controls the implementation of the robots functions depending on the challenge and environmental context.

  • Task Monitor: Monitors the implementation of the robots functions and sends the information to the task control feedback.
  • Task Control Feedback: Implements control action on the robot based on information received from the task monitor.
  • Task Control Feedforward: Contributes in the implementation of control actions on the robot depending on the state and the goal of the challenge.

2) Environmental Context: Semantic maze model.

3) Challenge Context: All information regarding the rules and the goals of the “A-Maze-ing challenge” are stored in this context.

4) Robot Context: This incorporates the low level specifications of the PICO robot.

5) Skills Context: Contains the above mentioned robot functionalities.

Interfaces

  • 1st
  • 2nd
  • 3rd
  • 4th