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Nathan Glover
Nathan Glover

Posted on • Originally published at devopstar.com

AWS RoboMaker - Raspberry Pi Bootstrap

#aws #tutorial #robomaker #raspberrypi

This post was originally written on DevOpStar. Check it out here

In the previous post AWS IoT Greengrass CloudFormation – Raspberry Pi we explored what is required to setup AWS Greengrass on a Raspberry Pi. This allowed us to manage a fleet of IoT edge devices using AWS CloudFormation.

With this in place we can begin to look at what we might be able to do with a Robot Fleet using another AWS service, AWS RoboMaker.

AWS RoboMaker Deployment Architecture

In this guide we'll be looking at how to build and bundle ROS applications specifically for the Raspberry Pi ARMHF architecture using Cloud9. The final goal is to have the bundled application deployed over AWS RoboMaker.

Prerequisites

Quick Greengrass Setup

If you haven't already setup a device with Greengrass, I urge you to go do that before completing this post, however if you want a burst fire round on setting it up, I've included everything needed in this repository too.

NOTE: I've stripped out some of the functionality that isn't required for RoboMaker from the greengrass.yaml we use below. Don't worry too much if you are still running it.

NOTE: *I've also added some policy permissions that will need to be added to the existing Greengrass stack. You can simply run update-stack instead of create-stack with the following (presuming your stack is named the same).

aws cloudformation create-stack \
    --stack-name "devopstar-rpi-gg-core" \
    --template-body file://aws/greengrass.yaml \
    --region "us-east-1" \
    --capabilities CAPABILITY_IAM
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Copy the certificates and config out and over to your Greengrass device.

cd aws
./greengrass.sh
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Using the appropriate Greengrass version from here install and setup Greengrass (referring to the previous guide when needed).

RoboMaker Create

The first step will be to create a brand new robot through RoboMaker. This process requires four parts:

  • RoboMaker Fleet Create
  • RoboMaker Robot Create
  • RoboMaker Application Create
  • RoboMaker Deployment Create

Luckily we're able to use CloudFormation for a good portion of this deployment currently. The only exception is the deployment phase which must be done using AWS CLI commands for now.

Have a look at the script we're about to run called robomaker.sh. It's responsibility it just to pull down the existing Greengrass group ID from the previously created Greengrass stack (called devopstar-rpi-gg-core) in my case.

greengrassGroupId=$(aws cloudformation describe-stacks \
    --stack-name devopstar-rpi-gg-core \
    --query 'Stacks[0].Outputs[?OutputKey==`GreengrassGroupId`].OutputValue' \
    --region ${AWS_REGION} \
    --output text)
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Using this Greengrass ID, we're able to setup a RoboMaker Fleet & Robot. by calling a CloudFormation template aws/robomaker.yaml that I've prepared earlier.

NOTE: There are a variety of other settings that can be overridden for the robot deployment. This includes the architecture type of the device. In our case it is a Raspberry Pi with arm7hf so ARMHF is selected, however your device might be something different.

aws cloudformation create-stack \
    --stack-name "devopstar-rpi-robot" \
    --template-body file://robomaker.yaml \
    --parameters \
        ParameterKey=GreengrassGroupId,ParameterValue=${greengrassGroupId} \
    --region ${AWS_REGION}

aws cloudformation wait stack-create-complete \
    --region ${AWS_REGION} \
    --stack-name "devopstar-rpi-robot"
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The final step in the script is to retrieve the name of the S3 bucket that is created for our RoboMaker deployments. This is the location where we'll be putting our deployment files and is available to our robots.

robotBucketName=$(aws cloudformation describe-stacks \
    --stack-name devopstar-rpi-robot \
    --query 'Stacks[0].Outputs[?OutputKey==`RobotAppBucket`].OutputValue' \
    --region ${AWS_REGION} \
    --output text)

echo "Put robot deployment files in s3://${robotBucketName}"
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To run all of the above steps in one hit, simply punch in the following commands.

cd aws
./robomaker.sh
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Then the deployment completes you'll be presented with a bucket that we will use in the next step to store our RoboMaker app.

# Put robot deployment files in s3://BUCKET_NAME
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Cloud9 Environment

To make life easier when working with ROS we will be making use of ROS Cloud9 Environments. This is effectively a cloud IDE with everything ROS setup for you.

Navigate to the developer IDE section in AWS RoboMaker and create a new instance with the following settings.

Cloud9 RoboMaker Environment

Once the environment starts up we're just going to open an example project by clicking "Robot Monitoring". You will begin to see a download occurring pulling down the sample project; and once complete you will be presented with a README.

Cloud9 RoboMaker Environment CloudWatch Project

sudo apt-get update
rosdep update
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Build & Bundle

x86_64

Building and bundling for x86_64 is really easy since we're already on an x86_64 system architecture.

cd ~/environment/CloudWatch/robot_ws
rosws update
rosdep install --from-paths src --ignore-src -r -y
colcon build
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We will use Colcon to build and bundle our robot application

cd ~/environment/CloudWatch/robot_ws
source install/local_setup.sh
colcon bundle
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armhf

Since we're trying to build for the Raspberry Pi we need to make sure we're cross compiling for armhf. Start off by building the cross-compile docker image (this step will take a while)

cd /opt/robomaker/cross-compilation-dockerfile/
sudo bin/build_image.bash
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Connect to the ros-cross-compile container

cd ~/environment/CloudWatch/robot_ws
sudo docker run -v $(pwd):/ws -it ros-cross-compile:armhf
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Now you're inside the cross-compilation docker container. Run the following commands to build the workspace

# build the workspace
cd ws
apt update
rosdep install --from-paths src --ignore-src -r -y

# These steps will take a while
colcon build --build-base armhf_build --install-base armhf_install
colcon bundle --build-base armhf_build --install-base armhf_install --bundle-base armhf_bundle --apt-sources-list /opt/cross/apt-sources.yaml
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RoboMaker Cloud9 colcon build and bundle

Finally, exit the container after the bundle is successful

exit
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Copy Bundle to S3

Copy the bundle to our S3 bucket using the following command

aws s3 cp armhf_bundle/output.tar s3://BUCKET_NAME/cloudwatch_robot/output.tar
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This will place the bundled output.tar in an S3 bucket location that will be used by RoboMaker during application deployments.

RoboMaker S3 Deployment of output.tar

NOTE: In production it would be a better idea to store this output file in versioned prefix locations (eg. s3://BUCKET_NAME/cloudwatch_robot/v1/output.tar)

RoboMaker App Deploy 

cd aws
./robomaker-app.sh
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The status of the deployment can be viewed in the RoboMaker deployment console.

RoboMaker Deployment status

Once the deployment is successful you should start to see CloudWatch logs coming through (in us-west-2 by default).

NOTE: It's very likely you will see mostly errors since you aren't deploying to a TurtleBot3 (the default the CloudWatch demo repo was originally created for)

RoboMaker Deployment CloudWatch logs

Cleanup

Before walking away from the project, make sure to remove the things we setup (especially the Cloud9 Environment).

Cloud9 Cleanup

The Cloud9 environment can be removed from the RoboMaker Environments section of the portal.

Cloud9 Remove Environment

CloudFormation Stacks Cleanup

The CloudFormation stacks can either be removed from the CloudFormation console or via CLI commands like the following:

aws cloudformation delete-stack \
    --stack-name "devopstar-rpi-robot-app-cloudwatch"

aws cloudformation delete-stack \
    --stack-name "devopstar-rpi-robot"

aws cloudformation delete-stack \
    --stack-name "devopstar-rpi-gg-core"
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