Community Question

The boards have been pretty quiet so I thought I would share what I am working on now.

***This is for robots using an on-board computer***
I have started making a plugin that is designed to use the xv-11 sensor, wheel radius and encoder counts per revolution of the wheels to make a map of the environment. It also uses the compass part of the 4-in-1 sensor sold on this site.

The map is currently stored in a SQLLite3 database. It is housed in the plugin directory. I don't know if this will be the final design or not but it is what I have working right now. There is a map table that is created by the user with the plugin. It contains the X coord, Y coord, tile and Counter fields. This will be used to store the map as it is being updated. The tile will be marked when the LIDAR recognizes something in that location of a certain intensity.

Quote:

The tile size is determined by the wheel diameter. If you have small wheels, you have small tiles. If you have large wheels, you have large tiles. The current environment that I am testing in has tiles that are about 4.19 inches by 4.19 inches. This is because I have wheels that are 4 inches in diameter and if you take the wheel diameter * pi / 3, you come up with 4.188790266.... I round this to 2 decimal places. If you had wheels that were 2 inches in diameter, you would have tiles that are 2.09 inches. If you had wheels that were 12 inches in diameter, the tiles would be 12.57 inches. The logic is that the wheels would be much smaller for robots in smaller environments and much larger for robots in larger environments. Larger wheels means faster moving robots and thus the updating of the environment would have to account for faster moving robots. The number of tiles in the map is determined by the configuration screen by setting the size you want your map to be. In the test, the map is 50 feet x 50 feet. Using a robot with 12 inch diameter wheels indoors in a 50x50 foot house could become problematic. These are all subject to change depending on testing.



Well the information quoted above has changed. I am in the US and as such am more comfortable using inches and feet, so I am making 1 inch tiles for everything. The wheel diameter is still important but not as important in laying out the grid. I am converting the mm readings from the LIDAR to inches and marking the squares. We will see how this works out and go from there. This, along with everything else is subject to change as I go through it all.

The map on the screen is loaded from the SQLLite3 database initially. As things are seen by the LIDAR, the map table is updated and the display is updated by marking the corresponding tile on the map.

Eventually my goal is to take this logic and use it in SLAM. I plan on starting with some simple SLAM using the RANSAC algorithm which is best used in indoor environments. This is because it estimates and creates landmarks based on straight lines. From there I will use the Extended Kalman Filter for data association. This allows the robot to recognize landmarks and then adjust its current position on the map based on these landmarks.

One of the reasons that I want to store this information in a SQLLite3 database is that this would allow me to have multiple maps housed in different tables. The configuration screen could be modified to allow the user to specify which environment the robot is in (office 1, Office 2, home, Mom's house for example). These maps would be stored in different tables and the user would just switch to the map that pertains to the current environment. Another thing that these multiple maps could be used for is to handle different floors of an office building, one for each floor.

The test map is about 13 meg in size. This isn't too large but is only based on a 50x50 foot house on a robot with 4 inch diameter wheels. If you were in a warehouse or large office building with a robot with small wheels, the size of the database could get really large I would imagine. The goal is to get this to work in a smaller environment, and then see what needs to be done to handle larger environments.

Eventually, I plan on incorporating a path finding algorithm. This shouldn't be too hard to do because it is done in video games like crazy. There is plenty of sample code to build from.

Anyway, that is what I am working on currently. I suspect it will take some time before I have something to share. This is a pretty ambitious project and I will post updates as I accomplish different things with it.

I am not sure if I will sell this plugin or make it freely available. This is something that I will decide after I know how it works in multiple environments. If it turns out to be simply amazing, I might sell it. If it just works, I will give it away for free and continue working on a final solution.

ZebraStripes
Commented August 2016
Hi There

Just to finish off my comment. I found a way to put teamviewer on the raspberry pi and so now I have remote access from my master pc to the 3D neato lidar output on my raspberry .

As noted this could perhaps more easily be done with a compact PC but my way is probably a bit cheaper ...

This is what you do:

1) use a raspberry 3 pi model b (or better) or vpython will not run

2) use a large SD card in your raspberry as the software is large in size. I used a 32GB card after smaller ones were not big enough.

3) use raspi-config in terminal to enable the experimental GL Driver graphics

4) install vpython (sudo apt-get install python-visual)

5) install exagear (which costs money) and teamviewer following these instructions:
https://eltechs.com/run-teamviewer-on-raspberry-pi/

7) Download lidar.py from:
http://www.getsurreal.com/products/xv-lidar-controller/xv-lidar-controller-visual-test

8) Identify the correct com port for the teensy and edit lidar.py

9) run python lidar.py from terminal

10) use teamviewer and enjoy lidar graphics on your master pc

Let me know if you have any problems but once you know the pitfalls it really is quite easy (ha!)

Cheers

Chris
CochranRobotics
Commented August 2016
Hey Chris,

Are you using the information for anything other than the display from lidar.py?

Thanks
David
ZebraStripes
Commented August 2016
Hi David

If I had time I would want to do more but progress for me is slow due to other less fun commitments like work.

I think there is a real market possibility for someone to write mapping and pathfinding software for the lidar if it were written in a flexible way to:

a) support the multiple lidars which exist
b) run on multiple machines (raspberry, pc etc)

Perhaps in python which seems quite efficient.

In the short term, at the very least I intend to make a serial connection between the EZB and the raspberry to do basic things like turn it on and off but this is so weak compared to the possibilities.

Cheers

Chris
CochranRobotics
Commented August 2016
Yea, was just wondering. It becomes difficult because different LIDAR's return data differently. They spin at different speeds and such. Python scripts can be used to determine which LIDAR it is possibly and adjust things as needed and all... I totally understand about work... I have been working on many different things right now so my experimentation and learning has been slow...
ZebraStripes
Commented August 2016
I think it is only matter of time before someone comes up with a good lidar script because the demand is out there. I would certainly be happy to pay for one. It seems daft for a whole bunch of people to write their own half-hearted scripts when it would be more sensible for a single more professional approach.

Anyway, for me now, I am going to progress my plans to put a whole bunch of arduino driven modular additions on to the roli including a geiger counter (just for fun). After that, I plan to find a second hand wild thumper or build my own and work out to auto-charge it. Then get it to climb up and down stairs which would be a fabulous challenge.

Once all that is done, then I will return to the lidar software issue. Probably several years at my rate of progress!
Question
AvatarCochranRobotics
Asked on Friday, January 1, 2016