UMAA Starter Kit

A starting point for developing to the UMAA standard with Connext.

• Overview
• UMAA Standard
  Breakdown of UMAA standard from a DDS perspective
• UMAA Data Types
• Best Practices
  Recommendations and general guidelines
• Example1: XML defined UMAA components
  USE CASE: Industrial grade infrastructure where you have separate Systems Engineering group to own XML files.
• Example2: Composed UMAA Service Template Classes
  USE CASE: Rapid prototyping and to maintain flexibility.
• Example3: Dynamic Data Pub/Sub
  USE CASE: Debugging/Simulation/Testing of UMAA topic data.
• CMAKE modules
• Record/Replay/Convert usage examples
  Examples of Record/Replay/Convert DDS Messages for offline analysis

Overview

Walkthrough here

This Starter Kit provides an entry point to developing with UMAA.
It highlights usage of a few UMAA defined Components to simulate
interaction between the different interfaces.

It showcases Connext's ability to easily instantiate UMAA components
using either the Modern C++ or the Python APIs.
It also highlights the option to manage DDS configuration of both systems with
a centralized xml or compose UMAA services from template classes.

UMAA Standard

Latest Version: 6.0 Distro A Download from AUVSI

The UMAA standard defines the following(as of 6.0):

• Middleware level:
  • Data model(~600 data types in an IDL format)
  • No QOS (Exception: Large Collections- PRESENTATION)
  • Topics(“Interfaces”) per “Service”.
• Application level:
  • Command state machine/handshaking("Flow Control")
  • Large data set synchronization("Large Collections")
  • Type extension("Generalizations/Specializations")
• Systems level:
  • "Components": Collection of "Interfaces" defined in the UMAA MBSE model.
    • This starter kit provides an xml definition of the Autopilot and USVNAV component
      DDS entities based on our interpretation of the v1.0 Component Definitions release.
    • There are currently ~40 components defined by UMAA of which 9 are Distro A.
      (resources/components/UMAA Component Definitions v1.0.pdf)

NOTE:
The application level requirements (i.e Flow Control/Large Collections/Generic-Specified types)
are outside of the current scope of this middleware reference starter kit.
Some application layer development would be required on top of the middleware infrastructure to
be compliant with the UMAA standard.

UMAA Data Types

UMAA defines ~ 600 data types. This is what is used to determine the "structure" of the data being transported.
With Connext, we use RTI Code Generator rtiddsgen (manual) to generate code per the API being used.
This code assists with construction and serialization/deserialization of these data structures.

C++11 data types

For the C++11 API, we generate helper headers and classes for all of the UMAA types
and then compile them into a single shared library.

This makes it more convenient to link your source code against when developing.

In this example we generate all the Type support code into the datamodel/cpp11_gen folder and
then use that code to create a shared lib.

Python data types

With Python, rtiddsgen converts the types into Python modules that we can then reference in our Python scripts.
For Python types there is a bug in RTIDDSGEN that doesn't resolve the include modules
paths correctly. (CODEGENII-2112)

The workaround is to export all the modules to a single folder and then we can add them to the PYTHONPATH.
You can find the Python types have been pre-generated and added to the datamodel/umaa/python_flat folder for this example.

Best Practices

Increase Network Buffers

UMAA data types can tend to be very large individually(compressed up to 1 KB each) and even
more so in aggregate.
During the automatic discovery process these are sent out to provide a definition of the
data structure to allow for deserialization of the messages.

On startup, this can cause local UDP buffers to get filled up and prevent the discovery sequence
from fully completing.

To mitigate this on Linux systems, one of the options is to increase the UDP buffers.

CMAKE modules

This repo pulls in a git submodule from rticonnextdds-cmake-utils.

The rticonnextdds-cmake-utils repo provides convenient CMAKE utils to find Connext, call rtiddsgen and pass in IDL files as an argument. Use /examples/CMakeLists.txt as a reference for creating a shared library for your UMAA IDL set.

Record/Replay/Convert usage examples

Connext includes a set of services that can capture selected DDS traffic and store in a SQLite database to allow for playback/conversion at a later date.

Some reference examples have been created for the workflow of recording, replaying and converting DDS messages.

Assets

• Recording Service Manual(7.3)
• Docker Container Image

Setup

• Install Connext Host per Connext Getting Started Guide
• Clone rticonnextdds-usecases-umaa repo
• Set NDDSHOME to your Connext Install Path.
• Publish DDS Data on Domain ID 1 using Example1's USVNAV Component

Record a "Deploy" scenario

This example logs a filtered subset of topics in a XCDR serialized format to a SQLite Database.
(Recording in a serialized format is more efficient for runtime usage.)

It also rolls over every 1GB and uses a formatted naming convention for every index.
Domain ID: 1

cd resources/services
./start_record.sh deploy

Record a "Debug" scenario

This example logs all topics in a JSON serialized(human readable) format to a SQLite Database.
Domain ID: 1

cd resources/services
./start_record.sh debug

Replay

When you "replay" DDS data what you are really doing is re-publishing the
messages that were originally logged.

As a writer of DDS data, your QoS then needs to meet or exceed any existing readers
within the current system.

You can include your systems QoS with the following 2 steps:

• Add the QoS XML file to the -cfgFile argument as per this example.
• Set the datawriter to use the desired QoS Profile like this.

Replay XCDR data

This example replays XCDR data logged from the "Deploy" scenario.
Domain ID: 1

cd resources/services
./start_replay.sh xcdr

Replay JSON data

This example replays JSON data logged from the "Debug" scenario.
Domain ID: 1

cd resources/services
./start_replay.sh json

Convert XCDR to JSON

This example converts XCDR data logged from the "Deploy" scenario to JSON.
Domain ID: 1

cd resources/services
./start_convert.sh xcdr_to_json

Convert XCDR to CSV

This example converts XCDR data logged from the "Deploy" scenario to CSV.
Domain ID: 1

cd resources/services
./start_convert.sh xcdr_to_csv