Mobile Robot Control 2020 Group 2: Difference between revisions
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For the selection of the algorithm used for pathplanning a table of pros and cons has been formulated, which inlcudes the computer performance index. A* is given an index number of 100. The walls and Dijkstra compute indices are an educated guess. The others are based on the amount of nodes used in a | For the selection of the algorithm used for pathplanning a table of pros and cons has been formulated, which inlcudes the computer performance index. A* is given an index number of 100. The walls and Dijkstra compute indices are an educated guess. The others are based on the amount of nodes used in a [https://www.researchgate.net/publication/320774676_Path_Planning_Algorithms_A_comparative_study study] | ||
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Revision as of 13:27, 26 May 2020
Group members
Marzhan Baubekova - 1426311
Spyros Chatzizacharias - 1467751
Arjun Menaria - 1419684
Joey Verdonschot - 0893516
Bjorn Walk - 0964797
Bart Wingelaar - 0948655
Design Document
Design document for the escape room challenge can be found here:
File:Mobile Robot Control Design Document Group2.pdf
Escape Room Challenge
Hospital Challenge
Pathplanning with 2 heuristics.
For the selection of the algorithm used for pathplanning a table of pros and cons has been formulated, which inlcudes the computer performance index. A* is given an index number of 100. The walls and Dijkstra compute indices are an educated guess. The others are based on the amount of nodes used in a study
| Algorithm | Compute index |
|---|---|
| A* | 100 |
| Rapidly-exploring random tree | 100 |
| Potential field algorithm | 40 |
| Dijkstra | 100 or higher |
| Wall following | 100000 |
| the one that only spyros had, but i dont remember | ? |
Path Planning
The algorithm that is chosen for the path planning is an A* algorithm. Before proceeding to algorithm, it is essential to transform map to a binary grid map. This step is done in Matlab and later translated to C++. There are two heuristic functions which are tested, namely diagonal and euclidian.
Localization
Logs
Meeting 1
Date: 28-04-20
Time: 10:00
Platform: MS Teams
Agenda
- Introduction meeting with the tutor
- Discuss assignments to be completed
- Discuss preliminary design and algorithm
Meeting notes
- The tutor's role is to guide and answer questions. The tutor is present at the weekly meetings.
- Robot description: the unit of the laserdata distance is [m] and the angle is in radians; the robot is about 40*20cm.
- Gitlab should be used.
- Wiki: At the end of every meeting a clear list has to be made of actions that should be done.
- Important dates and information about the first assignment: The design document should be hanged in on may 4th as PDF and text should not be mentioned on the wiki.
- Design document is the document that describes how the software will look like, which includes requirements, functions, components, specifications and interfaces.
- Requirements: robot's speed constraints and etc.
Meeting 2
Date: 01-05-20
Time: 14:00
Platform: MS Teams
Agenda
- Discuss the progress
- Discuss the design document
Meeting notes
- "Specifications and Requirments" section of the document design was discussed
- Finite State Machine was reviewed
- Action: meet on Monday (4th of May) to proof-read the report
Meeting 3
Date: 05-05-20
Time: 10:00
Platform: MS Teams
Agenda
- Questions about odometry data
- Question on identifying exit
- Questions on GitHub
- Discuss work to be done
Meeting notes
- The robot overshoots on rotating to the right. This is much worse than when rotating to the left.
- The tutor is going to look into the simulator since it might be a bug in there. He will let us know as soon as possible.
- Take into account that the exit could be aligned with the sidewall of the room meaning there is only one corner to identify instead of 2.
- Gitlab tutorial is online and should help us figure it out.
- Group members have to use git clone to get the master repository on their pc.
- Slip is not enabled by default. It has to be enabled in the config file when needed in simulation.
Work division
- Wall following algorithm -> Bjorn and Marzhan
- Wall finding and exit scanning -> Spyros and Arjun
- Wall alignment and exit corridor movement -> Bart and Joey
Next meeting
- Friday, May 8th, 2 pm group meeting on progress (without tutor).
- Monday, May 11th, 11 am final meeting before escape room challenge (with the tutor).
Meeting 4
Date: 11-05-20
Time: 11:00
Platform: MS Teams
Agenda
- Discuss problems of code.
- Question on exit width.
Meeting notes
- good progress has been made on the initial scanning
- Joey and Bart had the same section of code.
- The alligning at the exit can be improved
Work division
- Exit allignment -> Bjorn and Marzhan and Bart
- Wall finding and exit scanning -> Spyros and Arjun and Joey
Next meeting
- not determined yet.
Meeting 5
Date: 18-05-20
Time: 11:00
Platform: MS Teams
Agenda
- Discuss what went wrong in the Escape room competition.
- Discuss Hospital Chanllenge.
Meeting notes
- Code is corrected and escape room is succeeded
- Brainstorm on hospital challenge
- Outlining main parts of the hospital challenge
Work division
- Localization -> Bjorn and Joey and Marzhan
- Path Planning-> Spyros and Arjun and Bart
Next meeting
- 22-05-20 at 14:00 without tutor
Meeting 6
Date: 22-05-20
Time: 14:00
Platform: MS Teams
Agenda
- Discuss algorithm proposed by each subgroup.
- Discuss possible extention to object detection.
Meeting notes
- For path planning: A*
- For localization: particle filter
- Structure of the algorithm is constructed: main parts such as localization, path planning and object detection communicate through WorldModel and path planning also sends data to driveControl
Work division is the same
- Localization -> Bjorn and Joey and Marzhan
- Path Planning-> Spyros and Arjun and Bart
Next meeting
- 26-05-20 at 11:30 with tutor
Meeting 7
Date: 26-05-20
Time: 11:30
Platform: MS Teams
Agenda
- Discuss progress in path planning and localization.
Meeting notes
- For path planning, A* algorithm: advantage of diagonal over euclidian heurisic or vice versa.
- For localization: split and merge implementation for features extraction.
- Run localization all the time
Work division is the same
- Localization -> Bjorn and Joey and Marzhan
- Path Planning-> Spyros and Arjun and Bart
Next meeting
- 02-06-20 at 11:00 with tutor??