21 Sep 2014
ros
Below are 5 steps to getting the most out of ROS Answers, and hopefully giving the most
back to the community in the process:
1. Don't be afraid to ask a question
The name of the site may be "ROS Answers", but there is no point in having answers if
there are not questions. Often I find that people comment on old questions, or post
answers to old questions, hoping to get help for a possibly related problem. Your
comments will probably be missed by anyone who did not previously participate in that
question/answer thread, and posting an answer with a question is just bad etiquette.
If you have a question, open a new question!
2. But before you ask a question, check to see if someone has already asked and answered the exact same thing!
There are over
15,000 18000* questions on ROS Answers. There is a good
chance that if you have a common problem, it has already been asked, and probably answered.
The average time between posting a question and getting answer is probably several hours,
however, if you spend just a few minutes searching the site you might find your answer
immediately.
3. If you ask a question -- try to make sure other people will be able to find it some day by adding appropriate tags.
That search thingy in #2 depends on questions being properly tagged. Adding a few (useful)
tags will both help get you an answer faster, as well as making sure that the next person
with the same question can find your question and the answer to it. "ros" is probably not
a useful tag, the name of the package, node, or command in question would be good tags.
Including tags for the specific hardware you might be using could also be useful (for
instance "kinect" or "pr2")
4. Close button is evil. Karma is good.
This is probably the most misunderstood aspect of ROS Answers. People frequently post a
comment saying "thanks, that works" and then click the "close" button on the question
instead of selecting an answer. Please don't do this! Instead, click the checkmark next
to the question to select the answer to your question. You can only select the answer on
questions that you asked, however, if you find an answer to someone else's question that
helps you, you can give a little Karma by clicking the "up arrow". The answer to the
right here has been upvoted 26 times -- it must be pretty good.
The answers website really depends on Karma. New users have restrictions (unable to post
links, images, etc). New users NEED Karma to become more effective users. Power users need
Karma to be able to moderate the site, like retagging those questions where people didn't
get the tags right.
5. Finally, make sure somebody can actually maybe answer your question.
Good answers require good questions. If you get an error in the console, certainly include
that exact error into the question. A summary of the error, or "I got an error" are not
substitutes for the actual error or traceback. Tells us exactly what commands you ran.
Other things you probably want to include: what ROS version, operating system, and robot
you are running -- and if you aren't running from up-to-date debs from the OSRF apt repo,
you probably want to point out how you installed ROS.
* I started writing this post a few days after the 15000th question was posted. I finished
writing it 3000 questions later....
06 Sep 2014
robomagellan
ros
This post has been a long time coming -- I think I promised it to several HBRC members at
the July SIG...
I've frequently been asked "what computer do you use on your robots?", usually from someone
looking at a variety of sub-$100 ARM boards. ARM processors have come a long way, but for
a ROS computer, they are not the easiest choice. Austin Hendrix has done a lot of work to
get a
buildfarm up and running for ARM processors
-- but there is still a long way to go and many things will not work "out-of-the-box".
So my choice? Well, it's not under $100, but it is a very fast, fairly low power machine
(here, I define low-power in the sub-15W range). The latest generation of Intel NUC
(Next Unit of Computing) modules offer quite a few options for small Intel Core-based
omputers. I'm using the 4th-generation i3-based D34010WYK. This offers quite a bit of
compute power for ROS, especially when you consider that early TurtleBots ran on a
single-core Atom. I've used 35W TDP i3 processors on a number of mobile manipulation
problems and been able to run the OpenNI/OpenNI2-based drivers, the navigation stack and
MoveIt! without much difficulty. If you're looking for a bit more processor, there is an
i5-based version for $100 more.
Intel NUC (image from Intel NUC website)
These computers are sold as either a board (somewhat hard to find for sale) or as a kit
which includes the case. Either option requires memory, hard drive and wifi card to be
added. My setup is:
- 8GB Crucial Ballistix Sport SODIMM.
Whatever you choose, be sure it is 1.35V RAM -- the newer NUC models work ONLY with 1.35V RAM
(many modules are 1.5V).
- 120GB Crucial mSATA SSD. Intel
offers a larger case version of the NUC that fits a standard 2.5" drive, but the smaller
versions only take an mSATA drive.
- Intel 7260 Wireless-AC Card.
This card will work best with Ubuntu 14.04, older versions will need an updated kernel
(at least 3.13) to get working drivers. No need for antennas as they are already in the case.
These boards take 12-24V DC input, but are probably most efficient at 19V. I'm powering mine off
a 12V battery connected to a
Pololu 5A Step-Up Regulator
that is configured to output the desired 19V. My batteries will never get even close to 19V even
when fully charged, and so the regulator should not have any issues.
I would recommend installing Ubuntu 14.04 and using ROS Indigo for these machines. If you want
to use an older Ubuntu distro, you should definitely make sure your wifi card is compatible,
because the Ethernet port will not work with the drivers present on the 12.04 installer and you will
have to connect to ubuntu.com to update somehow. Another alternative is to look for a NUC based
on the 3rd-generation Intel Core processors, but these might be hard to locate.
24 Feb 2014
robomagellan
ros
Over a year ago, I posted about my RoboMagellan robot, and then nothing. It's been pretty
busy for the past year, but I finally got back to working on this robot. The control board
is now mostly functional, and I have integrated the IMU and GPS. I still have to get the
tilting laser assembly mounted and working, and come up with a permanent mount for the
camera, but earlier today I finally field tested the robot:
Drives well in grass, on pavement, and even has enough gusto to get up onto concrete
parking lot wheel stops (although it tends to then get stuck on top of said stop).
The forward odometry is good, but I still need to tune the turning odometry.
As far as ROS integration goes, I have the IMU, GPS, and wheels tied into ROS.
For decoding the GPS I'm using the
nmea_navsat_driver package,
which made things quite easy. I'm currently working on some tools for handling
localization and visualization while in a GPS coordinate frame (more to come on
that, but it is developed on top of
geodesy).
Code for the project is pretty minimal right now, but is hosted at
https://github.com/mikeferguson/robomagellan