Monthly Archives: June 2013

AVC – How difficult can it be ?

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Ever since the SparkFun AVC started a few years ago, I’ve wanted to enter. But living in the UK made it difficult to justify the expense of flying to Colorado for a robot competition. This year, purely coincidentally I was in the US for a conference the week before the competition. The opportunity was there to enter so I decided to build a robot and enter the SparkFun AVC 2013.

The AVC on paper sounds simple 🙂 … Build an autonomous vehicle that can navigate an obstacle course without human intervention. The course is timed and you get bonus points for achieving certain tasks (going under a hoop, going over a ramp, etc.).

I decided to enter the ground competition, as the aerial challenge sounded way more complex. I’ve never built an aerial robot, so I thought I stick to something I had experience in. I decided to base my robot on a radio controller car chassis. I had an HPi Racing Savage Flux XS, which was perfect. It’s a 4×4 mini monster truck, that’s fast and simple. Just two controls, steering and speed. In addition, the radio it comes with has three channels, so I could use the 3rd channel as a control to switch between radio control and autonomous control, and quickly switch back to radio control during testing in the event it went berserk and headed for a tree.

My bot has a GPS receiver to provide its current position, and a magnetometer to provide its current heading. A microcontroller controls the speed and steering servos and a Radio Control switch can switch between autonomous control and manual control using the third channel. In addition the course has obstacles, so I need some basic obstacle avoidance. I used a small sonar to provide the distance to obstacles directly in front.

I needed a way to monitor and debug the car while it was hurtling round my garden during testing. I decide to add an xBee so I could get basic debug information from the car in real time, and (as I did with the balance bot) write a simple PC desktop app to display them in a user friendly way.

AVC 2013 High level system diagram

AVC 2013 High level system diagram

SparkFun provide the course details with all the GPS coordinates. The course is roughly rectangular with four sides, a start finish straight, a side with 4 barrels as obstacles, a side with a hoop to go under for bonus points and a side with a small ramp to jump, again for bonus points. The course is about 200 feet square, with the course being about 20 feet wide. With basic GPS accuracy of 2-4m this made the challenge perfectly achievable … easy huh !? If only …

AVC 2013 Ground Course ((c) Sparkfun)

AVC 2013 Ground Course ((c) Sparkfun)

Initial components

I started with components I already had. An EM-406A GPS module and a Pololu 3D magnetometer breakout board. I bought a MaxSonar sonar from CoolComponents and an RC switch from Pololu to give me a failsafe control.

The initial plan was to use an Arduino, as I have lots of them and lots of experience programming them. As mentioned before, I like old school wire wrap for prototyping, so I prototyped a basic Arduino shield to tie the 3 sensors together.

The initial testing went well. I used a third party GPS library and magnetometer library to ingest the data and I could get a basic heading to a GPS waypoint, and get a bearing from the magnetometer on the bench. The PWM output worked controlling two test servos, so confidently I sketched a custom PCB to shrink the design and make it more feasible to fit in the RC car, so I could start field testing in the garden.

AVC 2013 Arduino Custom PCB v1.0 board

AVC 2013 Arduino Custom PCB v1.0 board

AVC 2013 Arduino Custom PCB with components

AVC 2013 Arduino Custom PCB with components

Once the PCB arrived I had the basic software running. The premise of the control system is to navigate to waypoints, so the GPS coordinates as used to calculate a bearing from the current position to the next way point. This is the heading the car needs to steer. However, the car is on rough terrain and will never steer in a straight line. The course the car is taking is provided by the magnetometer, which gives the bearing the car is pointing. To reach the waypoint the difference between the car’s heading and the GPS bearing need to be kept as close to zero. One of the best ways of doing this is to use a PID controller.

I had a basic control loop written, for the Arduino, which looks something like this pseudo code:

While(CurrentWaypoint < TotalWaypoints) {
  MagneticHeading = GetMagnetometerHeading();
  GPSLocation = GetGPSLocation();
  GPSHeading = GetGPSHeadingToWayPoint(GPSLocation,WayPoint);
  PID_input = MagneticHeading – GPSHeading;
  ComputePID();
  SetSteering(PID_output);
  If (DistanceToWaypoint < 2m) then CurrentWaypoint++;
}

This should steer the car in a straight line from wherever it is, to a defined GPS waypoint. Once it gets within 2m of the way point, it moves on to the next waypoint. Once all the waypoints have been reached, it ends.

This is when the problems began…

Other posts in this series :

BalanceBot – Console App

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Debugging Arduino programs can be difficult, as the only easy output method is a serial console. With lots of debug messages the console soon becomes full and difficult to read efficiently. The biggest issue is the console scrolls, so with lots of output the text scrolls past too fast to read. One solution is to write a simple app on your laptop/desktop that listens to the serial data and displays it in an app with a better layout. You can create individual text boxes that just display the values of key variables, and the app can scan the serial stream looking for these variables and update the text box every time it sees a new value.

Depending on your microcontroller code purpose, you can also chose more appropriate visual representations of your debug variables. For example, you could show an arrow on a compass to represent the value you get from a magnetometer, you can plot a point on a Google map page in and HTML control to show the position you get from a GPS, and you can display green and red dots to show the value of switches, etc.

I use Visual Basic, just because I find it easy. You can design the visual layout of the app easily, and the code is very simple, but *any* programming language will work. Pick one you are most familiar with. You don’t want to waste time building the debugging console, when you could spend that time debugging your microcontroller code.

I use two techniques in the serial protocol; I prefix each line with a symbol that defines what type of data the line contains and I use name / value pairs for data to display.

e.g.

#Init Motor Driver
#Init Wire library
#Init IMU
#Get first YPR
#Set initial Input variable
#Init IMU Setpoint
#Exit Setup
$StatusA = 1011
$CountA = 4294967255
$StatusB = 11101010
$CountB = 0
$Yaw = -130.54
$Pitch = -6.03
$Roll = 23.43
$Input = 23.4341
$Output = -400
$OutputA = -400
$OutputB = -400
$Heading = -137
$Button = 1

# – denotes debug messages. I add a time stamp to them and display them in a “messages” text box.

$ – denotes a name / value pair. The value is displayed in a text box for that name.

Instead of a difficult to read scrolling text window, I now have a stable windows app that displays each variable I want to track in an easy to read layout. In addition, I have a log of messages, with time stamps, I can scroll back through looking for interesting events. Finally, you can also decide to output some values are different frequencies, i.e. the fast changing values every 500ms, and the slow changing values every 5 seconds. The app also shows the current value for everything.

You can also get your microcontroller to listen to the input serial stream and use the app to send commands to your device. Add an XBee and now your microcontroller is wirelessly remotely monitored and controlled by your app on your desktop !

BalanceBot – Laser cut Acrylic

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The frame of the robot is built from MicroRax but it has no “sides”. I needed to mount some switches, etc. plus I wanted to mount the Arduino board securely and the two mounting holes in the Arduino are at very specific locations which would be better secured to a flat surface. They didn’t line up with the MicroRax.

The initial prototype had a hardboard base, but I thought I’d use the opportunity to learn how to get laser cut plastic. I found a supplier, Ponoko, which had a very simple interface. A lot of laser cutting houses use AutoCAD or Illustrator file formats to define the shape to cut. As I didn’t have an applications that can produce these, I liked Ponoko, as it used PNG. This can be generated huge number of apps, a lot of which are free.

Ponoko provide a sample template. The format is very straight forward. The colour of the line in the file defines the cut the laser will make. E.g. Cut, engrave, etc. They also have a huge array of materials, including acrylic, leather, card, wood, paper, rubber, etc.

I designed a top and a bottom. The bottom has a hole for the cables. The top is engraved (no reason other than I wanted to try it and it looks cool :-)) I didn’t get the holes for the switches laser cut, I drilled them, as I didn’t know at the time what switches I would be using.

Hardboard BalanceBot floor with Arduino PCB mounts

Hardboard BalanceBot floor with Arduino PCB mounts

PNG file used to laser cut the acrylic. Different coloured lines represent different types of cut or engraving.

PNG file used to laser cut the acrylic. Different coloured lines represent different types of cut or engraving.

Laser Cut Acryilic sheets. Cut by Ponoko.

Laser Cut Acryilic sheets. Cut by Ponoko.

Laser cut acryilic top with laser engraving

Laser cut acryilic top with laser engraving

The acrylic panels made the robot look very professional, in fact people ask me where I bought it 🙂

The panels made mounting the boards and switches trivial. I used self-adhesive PCB supports for the Arduino. The holes on the Arduino are 3.2mm. I found PCB supports 6.4mm high from RS which fitted perfectly. The Acryilic is easy to drip, so I hand drilled holes for the switches and buttons.