AUVSI SUAS Interoperability

Build Status

Repository for the Interoperability System used in the Association for Unmanned Vehicle Systems International (AUVSI) Student Unmanned Aerial System (SUAS) Competition.

Repository Contents:

Table of Contents:

Getting Started

This section describes how to go from setting up the Interoperability Server to completing interop tasks with the provided client library. The following code and command examples work with the competition's host operating system, Ubuntu.

Prerequisites

The Interoperability System builds on top a set of standard technologies. These technologies should be learned and understood prior to using the Interoperability System. The following are resources the reader can use to learn these technologies.

Computers and Networking

This subsection describes the computer and networking setup at competition. The teams should replicate this setup to test their integration.

IP Addresses, Username, & Password

At Check-In and Orientation, teams will be given a static IP address, a DHCP IP address range, the server IP address and port, a username, and a password. The static IP address (e.g. 10.10.130.100) will be a single address unique to the team which can be used to connect to the system. The DHCP range will be a common range that will be provisioned to teams automatically by the interop router. The router will be on the subnet 10.10.130.XXX with subnet mask 255.255.255.0. The server IP address and port will be used to communicate with the interop server (e.g. http://10.10.130.2:8000). The username (e.g. testuser) and password (e.g. testpass) will be the interop server login credentials required to execute requests. The username will not be for a superuser/administrator account on the server.

Interop Hardware

The hardware consists of a router and a computer. The router will be configured to have a static IP address range, and a DHCP IP address range. All connected judge computers will be at a static IP address. The judges may also use network configuration, like VLANs, to further isolate network traffic.

The judges have additional hardware to improve reliability of the interop deployment. The judges use an additional computer to act as a black-box prober which continuously executes requests to validate availability. The judges also use UPS battery backups to prevent unavailability due to generator power loss.

During Mission Setup, the teams will be provided a single ethernet cord. This cord will connect the team's system to the interop router, which will be connected to the interop server. The mission clock will end once the team has evacuated the runway and returned this ethernet cord.

Team Hardware

The judges recommend that teams use a router to have a separate subnet. The judge provided ethernet cord will then connect a LAN port on the interop router to the WAN port on the team's router. This will allow multiple team computers to communicate with the interop server at the same time. This will also allow a single computer to simultaneously communicate with the interop server and other team computers.

The teams will need at least one computer to communicate with the interop server. The judges recommend that teams leverage the provided client library and tools, which are available in the client Docker image. Teams may also integrate directly via the HTTP + JSON protocol.

Setup the Host Computer

Install docker with the Docker Engine Installation guide.

Install docker-compose with the Docker Compose Installation guide.

Install git with the Git Installation guide.

From the command line you should have access to docker, docker-compose, and git. Commands and scripts below will depend on these tools.

Interop Git Repo

The interop server is developed using Git. Clone the repo to download scripts.

git clone https://github.com/auvsi-suas/interop.git

Now change directories into the interop folder. The following commands assume they are run from the interop folder.

cd interop

Docker Images

The Interoperability System is released to teams as Docker images and Docker Compose YAML configurations. These can be used to run the server and client tools with minimal setup.

auvsisuas/interop-server

First Time Setup

Change into the server subdirectory of the Git repo.

cd interop/server

Create the interop server's database.

sudo ./interop-server.sh create_db

Load initial test data into the server. This provides access to a default admin account (u: testadmin, p: testpass) and a default team account (u: testuser, p: testpass). This will also load a sample mission into the server.

sudo ./interop-server.sh load_test_data
Run the Server

Run the server on port 8000, so it can be accessed in a local web browser at localhost:8000. Other machines on the same network can replace localhost with the host computer's IP address.

sudo ./interop-server.sh up

The server will run until stopped using Ctrl-C.

View Server Log

Logs are also available via volumes on the host computer under volumes/var/log/uwsgi/interop.log.

Upgrade the Server

Upgrade the Server by downloading new images, deleting the old containers, and starting the server again.

sudo ./interop-server.sh upgrade

Note server data is persisted due to volumes. If the existing data causes an issue, you can delete it (see next section).

Delete Server Data

While the server isn't running, you can delete the server data by deleting the volumes and containers. Note this action is permanent.

sudo ./interop-server.sh rm_data

After deleting the data, you will need to follow First Time Setup instructions.

auvsisuas/interop-client

Create Container & Start Shell

Change into the client subdirectory of the Git repo.

cd interop/client

The interop client library and tools are provided as a Docker image and can be run as a Docker container. The repo provides a script to run the container in a standard way: it creates the container and starts a pre-configured shell.

sudo ./interop-client.sh run
Get Teams

The client image provides a script to request the status of teams from the interoperability server, and it can be executed from the container shell. The following shows how to execute it for the default testing user (testuser) if the interop server was at 10.10.130.2:8000.

./tools/interop_cli.py \
    --url http://10.10.130.2:8000 \
    --username testuser \
    teams
Get Mission

The client image provides a script to request mission details from the interoperability server, and it can be executed from the container shell. The following shows how to execute it for the default testing user (testuser) if the interop server was at 10.10.130.2:8000, requesting for mission ID 1.

./tools/interop_cli.py \
    --url http://10.10.130.2:8000 \
    --username testuser \
    mission \
    --mission_id 1
Upload Objects

The client image provides a script to upload detected objects to the interop server from a directory of files. Each object to be uploaded gets 2 files in the directory, both of which start with a number unique to the object, where one has the extension json, and the other has either the extension jpg or png. The json extension file must contain a JSON formatted object data conforming to the POST /api/odlcs data segment. A jpg extension file must be a JPEG image, and a png extension file must be a PNG image. The following shows how to upload objects from the client container shell.

Example folder structure with two objects:

Example JSON file:

{
  "type": "standard",
  "latitude": 38.1478,
  "longitude": -76.4275,
  "orientation": "n",
  "shape": "star",
  "background_color": "orange",
  "alphanumeric": "C",
  "alphanumeric_color": "black"
}

Exaxmple command to upload:

./tools/interop_cli.py \
    --url http://10.10.130.2:8000 \
    --username testuser \
    odlcs \
    --odlc_dir /path/to/object/directory

Continuous Integration

By default, Docker will use the latest tag which corresponds to the most recently uploaded image. Using the latest tag will ensure you have the most up-to-date code. For continuous integration (CI), however, this will cause flakiness in CI reporting as your tests are unlikely to handle API or implementation changes without manually adaptating your system. For CI, you'd prefer to upgrade the container image version manually, adapting the system at the same time (e.g. same commit).

The competition Docker images are tagged with the release month so teams can manually specify versions for CI. These tags should be available for at least 3 months, allowing teams to use last month's frozen version for CI and to have a month to upgrade between versions. Tags may be deleted after 3 months to ensure teams upgrade. Closer to competition, tags younger than 3 months may be deleted to ensure all changes are applied before competition.

To use a specific version, append the version to the named Docker image:

sudo docker pull auvsisuas/interop-server:2018.10
sudo docker pull auvsisuas/interop-client:2018.10

You can find the available tags here:

Mission Configuration

This section describes how to configure a mission as an administrator on a running interop server.

Preconfigured Users

The interop server Docker image comes with 2 users preconfigured: a test team user (testuser, testpass), and a test admin user (testadmin, testpass). At competition, the judges will have a secret admin account (testadmin will be deleted), and the teams will be given a new team account (not testuser with testpass). Don't confuse the capabilities of the two accounts! At competition you will not have access to an admin account, so you will not be able to see the following admin dashboards. Don't hard-code the username and password!

Admin Web Login

The interop server has an admin webpage that can be used to configure the server. Navigate to http://localhost:8000 in a web browser. You may need to replace localhost:8000 if you've configured the setup differently. This will prompt for an admin account login, so enter the preconfigured user: testadmin with password testpass.

SUAS Admin Dashboard

After login it will show the SUAS made admin dashboard. It will have a navigation bar with system-wide and mission-specific links. The homepage for the dashboard will also list the current missions, and should show the single mission which comes with the image. If you click the mission, you will be brought to a mission-specific dashboard.

Django Admin Dashboard

From the SUAS Admin Dashboard, you can use the menu System > Edit Data to open the Django Admin dashboard. You should know how to use this interface from the Prerequisite work.

Mission Configuration

To configure a mission, create or edit the MissionConfig object to specify the desired flight boundaries, waypoints, true objects (for grading base objects), etc.

Takeoff or Landing Events

When a team takes off and when a team lands, the interop judge creates a TakeoffOrLandingEvent to mark the event. This is used to evaluate UAS telemetry rates, waypoints, and collisions only while airborne.

Interop Integration

This section provides examples for how to integrate with the interop server. You are allowed to create custom integrations, so long as they follow the API.

Interop Client Docker Image

The competition provides a Docker image containing all of the client integration tools. You can use these tools directly to integrate, or use the Docker image as a base image for your own Docker images.

Interop Client Library

The competition provides a client library to make integration easier. It is recommended that teams use this library to create a high-quality integration. You can install the client library by executing setup commands listed here.

To create a client object, import the interop module and construct the object with the server URL, your username, and your password. The competition provides two client objects: one which does synchronous requests, and another which does asynchronous requests. The following examples show how to use the synchronous form.

from auvsi_suas.client import client
from auvsi_suas.proto import interop_api_pb2

client = client.Client(url='http://127.0.0.1:8000',
                       username='testuser',
                       password='testpass')

The following shows how to request the status of teams.

teams = client.get_teams()
print(teams)

The following shows how to request the mission details.

mission = client.get_mission(1)
print(mission)

The following shows how to upload UAS telemetry.

telemetry= interop_api_pb2.Telemetry()
telemetry.latitude = 38
telemetry.longitude = -76
telemetry.altitude = 100
telemetry.heading = 90

client.post_telemetry(telemetry)

The following shows how to upload a object and it's image.

odlc = interop_api_pb2.Odlc()
odlc.type = interop_api_pb2.Odlc.STANDARD
odlc.latitude = 38
odlc.longitude = -76
odlc.orientation = interop_api_pb2.Odlc.N
odlc.shape = interop_api_pb2.Odlc.SQUARE
odlc.shape_color = interop_api_pb2.Odlc.GREEN
odlc.alphanumeric = 'A'
odlc.alphanumeric_color = interop_api_pb2.Odlc.WHITE

odlc = client.post_odlc(odlc)

with open('path/to/image/A.jpg', 'rb') as f:
    image_data = f.read()
    client.put_odlc_image(odlc.id, image_data)

For more details on the API, see the code here.

MAVLink (ArduPilot) Integration

The Interop Client Image comes with MAVLink integration. Teams can use the interop_cli.py command line tool to forward MAVLink messages to the interoperability server.

MavProxy

The competition recommends using MavProxy to tee traffic, so that telemetry goes to the Ground Control Station (e.g. Mission Planner) and also to the interop_cli.py tool. See the Getting Started guide for how to install and use the proxy. The specific command to use depends on the setup. An example invocation to proxy one input stream to two output streams:

mavproxy.py --out=127.0.0.1:14550 --out=127.0.0.1:14551
Interop Forwarding

You can use the inteorp_cli.py to read a MAVLink input stream, convert to telemetry messages, and forward to the interoperability server. From the Interop Client Docker Image:

./tools/interop_cli.py \
    --url http://10.10.130.2:8000 \
    --username testuser \
    mavlink \
    --device 127.0.0.1:14550
Ground Control Station

You can use a GCS like Mission Planner to control the MAVLink-based autopilot. Configure the program to read the other MavProxy output port (in the example, 14551).

Performance Evaluation

Once you have integrated with the Interoperability System, you should then validate the integration by performing an end-to-end test. This should include using the automatic evaluation the judges will use, which is provided as part of the interop server.

Note that proper evaluation requires a representative MissionConfig, which will include things like the flight boundaries and the details for the true object detections.

Provide Human Judge Data

The first step is to provide the manual judge data. Go to System > Edit Data. Select Mission judge feedbacks >> add. Fill out the object with the mission, user, and details about the team's performance, and then save.

Review Object Imagery

The second step is to review any object imagery provided. This is used to review whether the provided image is acceptable, and whether human graded features are correct (e.g. emergent object description). It is not used to grade whether the object details are correct (done automatically). Go to the Mission Dashboard, and then use the menu Mission > Review Objects. Click on a object ID to see the image and details, and then approve or reject the image, and if applicable the emergent description.

Automatic Evaluation

The third step is to run the automatic evaluator. Use the menu Mission > Evaluate Teams. Select which users you want to evaluate, then hit Evaluate. This will generate a zip file containing Json formatted feedback, and a CSV file containing all team's data. Note that this operation filters superuser accounts- testing must be done with a nonsuperuser (team) account. This output contains the MissionEvaluation and MultiOdlcEvaluation data.

API Specification

This section describes the interoperability interface that is implemented by the AUVSI SUAS competition server. Teams should use this documentation to integrate with the competition server.

Hostname & Port

The competition will specify the hostname and port of the server at the competition. The hostname will be the IP address of the computer on which the server is running, and the port will be the port selected when starting the server. Teams must be able to specify this to their system during the mission. The hostname can also be the hostname given to the computer. The hostname "localhost" is a reserved name for the local host, and it resolves to the loopback IP address 127.0.0.1. An example hostname and port combination is 192.168.1.2:8080.

For testing, teams can setup the interop server on a computer they own and use the computer's hostname and port to form an address.

Relative URLs vs Full Resource URL

The relative URLs (endpoints) are described further in the following sections. The interface defined in this document is what will be used at the competition. Only slight changes may be made leading up to the competition to fix bugs or add features. Teams should synchronize their code and check this documentation for updates. An example relative URL is /api/server_info.

The full resource URL is the combination of the hostname, port, and relative URL. This is the URL that must be used to make requests. An example full resource URL is "http://192.168.1.2:80/api/login".

Status Codes

Some of the HTTP status codes you may receive when using this API:

Endpoints

Below are all of the endpoints provided by the server, displayed by their relative URL, and the HTTP method with which you access them.

Some endpoints take JSON requests or return JSON responses. The format of the JSON data is defined in the Interop API Proto.

User Login

POST /api/login

Teams must login to the competition server by making an HTTP POST request with a LoginRequest JSON formatted proto. Teams only need to make a login once before any other requests. The login request, if successful, will return cookies that uniquely identify the user and the current session. Teams must send these cookies to the competition server in all future requests.

Example Request:

POST /api/login HTTP/1.1
Host: 192.168.1.2:8000
Content-Type: application/json

{
    "username": "testadmin",
    "password": "testpass"
}

Example Response:

HTTP/1.1 200 OK
Set-Cookie: sessionid=9vepda5aorfdilwhox56zhwp8aodkxwi; expires=Mon, 17-Aug-2015 02:41:09 GMT; httponly; Max-Age=1209600; Path=/

Login Successful.

Teams

GET /api/teams

This endpoint gets the status of teams. Returns a list of TeamStatus JSON formatted proto.

Example Request:

GET /api/teams HTTP/1.1
Host: 192.168.1.2:8000
Cookie: sessionid=9vepda5aorfdilwhox56zhwp8aodkxwi

Example Response:

Note: This example reformatted for readability; actual response may be entirely on one line.

HTTP/1.1 200 OK
Content-Type: application/json
[{
  "team": {
    "id": 2,
    "username": "testuser",
    "name": "Team Name",
    "university": "Team University"
  },
  "inAir": false,
  "telemetry": {
    "latitude": 0.0,
    "longitude": 0.0,
    "altitude": 0.0,
    "heading": 0.0
  },
  "telemetryId": "1278",
  "telemetryAgeSec": 1.064382,
  "telemetryTimestamp": "2019-10-05T20:42:23.643989+00:00"
}]

Missions

GET /api/missions/(int:id)

This endpoint gets the details about a mission with id id, and returns a Mission JSON formatted proto.

Example Request:

GET /api/missions/1 HTTP/1.1
Host: 192.168.1.2:8000
Cookie: sessionid=9vepda5aorfdilwhox56zhwp8aodkxwi

Example Response:

Note: This example reformatted for readability; actual response may be entirely on one line.

HTTP/1.1 200 OK
Content-Type: application/json

{
  "id": 1,
  "lostCommsPos": {
    "latitude": 38.144778,
    "longitude": -76.429417
  },
  "flyZones": [
    {
      "altitudeMin": 100.0,
      "altitudeMax": 750.0,
      "boundaryPoints": [
        {
          "latitude": 38.1462694444444,
          "longitude": -76.4281638888889
        },
        {
          "latitude": 38.151625,
          "longitude": -76.4286833333333
        },
        {
          "latitude": 38.1518888888889,
          "longitude": -76.4314666666667
        },
        {
          "latitude": 38.1505944444444,
          "longitude": -76.4353611111111
        },
        {
          "latitude": 38.1475666666667,
          "longitude": -76.4323416666667
        },
        {
          "latitude": 38.1446666666667,
          "longitude": -76.4329472222222
        },
        {
          "latitude": 38.1432555555556,
          "longitude": -76.4347666666667
        },
        {
          "latitude": 38.1404638888889,
          "longitude": -76.4326361111111
        },
        {
          "latitude": 38.1407194444444,
          "longitude": -76.4260138888889
        },
        {
          "latitude": 38.1437611111111,
          "longitude": -76.4212055555556
        },
        {
          "latitude": 38.1473472222222,
          "longitude": -76.4232111111111
        },
        {
          "latitude": 38.1461305555556,
          "longitude": -76.4266527777778
        }
      ]
    }
  ],
  "waypoints": [
    {
      "latitude": 38.1446916666667,
      "longitude": -76.4279944444445,
      "altitude": 200.0
    },
    {
      "latitude": 38.1461944444444,
      "longitude": -76.4237138888889,
      "altitude": 300.0
    },
    {
      "latitude": 38.1438972222222,
      "longitude": -76.42255,
      "altitude": 400.0
    },
    {
      "latitude": 38.1417722222222,
      "longitude": -76.4251083333333,
      "altitude": 400.0
    },
    {
      "latitude": 38.14535,
      "longitude": -76.428675,
      "altitude": 300.0
    },
    {
      "latitude": 38.1508972222222,
      "longitude": -76.4292972222222,
      "altitude": 300.0
    },
    {
      "latitude": 38.1514944444444,
      "longitude": -76.4313833333333,
      "altitude": 300.0
    },
    {
      "latitude": 38.1505333333333,
      "longitude": -76.434175,
      "altitude": 300.0
    },
    {
      "latitude": 38.1479472222222,
      "longitude": -76.4316055555556,
      "altitude": 200.0
    },
    {
      "latitude": 38.1443333333333,
      "longitude": -76.4322888888889,
      "altitude": 200.0
    },
    {
      "latitude": 38.1433166666667,
      "longitude": -76.4337111111111,
      "altitude": 300.0
    },
    {
      "latitude": 38.1410944444444,
      "longitude": -76.4321555555556,
      "altitude": 400.0
    },
    {
      "latitude": 38.1415777777778,
      "longitude": -76.4252472222222,
      "altitude": 400.0
    },
    {
      "latitude": 38.1446083333333,
      "longitude": -76.4282527777778,
      "altitude": 200.0
    }
  ],
  "searchGridPoints": [
    {
      "latitude": 38.1444444444444,
      "longitude": -76.4280916666667
    },
    {
      "latitude": 38.1459444444444,
      "longitude": -76.4237944444445
    },
    {
      "latitude": 38.1439305555556,
      "longitude": -76.4227444444444
    },
    {
      "latitude": 38.1417138888889,
      "longitude": -76.4253805555556
    },
    {
      "latitude": 38.1412111111111,
      "longitude": -76.4322361111111
    },
    {
      "latitude": 38.1431055555556,
      "longitude": -76.4335972222222
    },
    {
      "latitude": 38.1441805555556,
      "longitude": -76.4320111111111
    },
    {
      "latitude": 38.1452611111111,
      "longitude": -76.4289194444444
    },
    {
      "latitude": 38.1444444444444,
      "longitude": -76.4280916666667
    }
  ],
  "offAxisOdlcPos": {
    "latitude": 38.145111,
    "longitude": -76.427861
  },
  "emergentLastKnownPos": {
    "latitude": 38.145111,
    "longitude": -76.427861
  },
  "airDropBoundaryPoints": [
    {
      "latitude": 38.14616666666666,
      "longitude": -76.42666666666668
    },
    {
      "latitude": 38.14636111111111,
      "longitude": -76.42616666666667
    },
    {
      "latitude": 38.14558333333334,
      "longitude": -76.42608333333334
    },
    {
      "latitude": 38.14541666666667,
      "longitude": -76.42661111111111
    }
  ],
  "airDropPos": {
    "latitude": 38.145848,
    "longitude": -76.426374
  },
  "ugvDrivePos": {
    "latitude": 38.146152,
    "longitude": -76.426396
  },
  "stationaryObstacles": [
    {
      "latitude": 38.146689,
      "longitude": -76.426475,
      "radius": 150.0,
      "height": 750.0
    },
    {
      "latitude": 38.142914,
      "longitude": -76.430297,
      "radius": 300.0,
      "height": 300.0
    },
    {
      "latitude": 38.149504,
      "longitude": -76.43311,
      "radius": 100.0,
      "height": 750.0
    },
    {
      "latitude": 38.148711,
      "longitude": -76.429061,
      "radius": 300.0,
      "height": 750.0
    },
    {
      "latitude": 38.144203,
      "longitude": -76.426155,
      "radius": 50.0,
      "height": 400.0
    },
    {
      "latitude": 38.146003,
      "longitude": -76.430733,
      "radius": 225.0,
      "height": 500.0
    }
  ],
  "mapCenterPos": {
    "latitude": 38.145103,
    "longitude": -76.427856
  },
  "mapHeight": 1200.0
}

UAS Telemetry

POST /api/telemetry

Teams make requests to upload the UAS telemetry to the competition server. Takes a Telemetry JSON formatted proto.

Each telemetry request should contain unique telemetry data. Duplicated data will be accepted but not evaluated.

Example Request:

POST /api/telemetry HTTP/1.1
Host: 192.168.1.2:8000
Cookie: sessionid=9vepda5aorfdilwhox56zhwp8aodkxwi
Content-Type: application/json

{
  "latitude": 38,
  "longitude": -75,
  "altitude": 50,
  "heading": 90
}

Object Detection, Localization, Classification (ODLC)

POST /api/odlcs

This endpoint is used to upload a new odlc for submission. All odlcs uploaded at the end of the mission time will be evaluated by the judges. Takes a Odlc JSON formatted proto and returns the durable ODLC with assigned ID.

Most of the odlc characteristics are optional; if not provided in this initial POST request, they may be added in a future PUT request. Characteristics not provided will be considered left blank. Note that some characteristics must be submitted by the end of the mission to earn credit for the odlc.

Example Request:

POST /api/odlcs HTTP/1.1
Host: 192.168.1.2:8000
Cookie: sessionid=9vepda5aorfdilwhox56zhwp8aodkxwi
Content-Type: application/json

{
  "mission": 1,
  "type": "STANDARD",
  "latitude": 38,
  "longitude": -76,
  "orientation": "N",
  "shape": "RECTANGLE",
  "shapeColor": "RED",
  "autonomous": false
}

Example Response:

Note: This example reformatted for readability; actual response may be entirely on one line.

HTTP/1.1 200 OK
Content-Type: application/json

{
  "id": 1,
  "mission": 1,
  "type": "STANDARD",
  "latitude": 38,
  "longitude": -76,
  "orientation": "N",
  "shape": "RECTANGLE",
  "shapeColor": "RED",
  "autonomous": false
}
PUT /api/odlcs/(int:id)

Update odlc id id. This endpoint allows you to specify characteristics that were omitted in POST /api/odlcs, or update those that were specified. Takes an Odlc JSON formatted proto and returns the updated ODLC in the same format.

Example Request:

PUT /api/odlcs/1 HTTP/1.1
Host: 192.168.1.2:8000
Cookie: sessionid=9vepda5aorfdilwhox56zhwp8aodkxwi
Content-Type: application/json

{
  "id": 1,
  "mission": 1,
  "type": "STANDARD",
  "latitude": 38,
  "longitude": -76,
  "orientation": "N",
  "shape": "CIRCLE",
  "shapeColor": "RED",
  "autonomous": false
}

Example Response:

Note: This example reformatted for readability; actual response may be entirely on one line.

HTTP/1.1 200 OK
Content-Type: application/json

{
  "id": 1,
  "mission": 1,
  "type": "STANDARD",
  "latitude": 38,
  "longitude": -76,
  "orientation": "N",
  "shape": "CIRCLE",
  "shapeColor": "RED",
  "autonomous": false
}
GET /api/odlcs

This endpoint is used to retrieve a list of odlcs uploaded. Returns a list of Odlc JSON formatted proto.

This endpoint will only return up to 100 odlcs. It is recommended to remain below 100 odlcs total (there certainly won't be that many at competition!). If you do have more than 100 odlcs, individual odlcs may be queried with GET /api/odlcs/(int:id).

Example Request:

GET /api/odlcs HTTP/1.1
Host: 192.168.1.2:8000
Cookie: sessionid=9vepda5aorfdilwhox56zhwp8aodkxwi

Example Response:

Note: This example reformatted for readability; actual response may be entirely on one line.

HTTP/1.1 200 OK
Content-Type: application/json

[
  {
    "id": 1,
    "mission": 1,
    "type": "STANDARD",
    "latitude": 38,
    "longitude": -76,
    "orientation": "N",
    "shape": "RECTANGLE",
    "shapeColor": "RED",
    "autonomous": false
  },
  {
    "id": 1,
    "mission": 2,
    "type": "OFF_AXIS",
    "latitude": 39,
    "longitude": -75,
    "orientation": "S",
    "shape": "CIRCLE",
    "shapeColor": "BLUE",
    "autonomous": true
  }
]

The endpoint also takes an optional GET parameter to restrict the returned ODLCs to the ones for a specific mission.

Example Request:

GET /api/odlcs?mission=1 HTTP/1.1
Host: 192.168.1.2:8000
Cookie: sessionid=9vepda5aorfdilwhox56zhwp8aodkxwi
GET /api/odlcs/(int:id)

Details about a odlc id id. This simple endpoint allows you to verify the uploaded characteristics of a odlc. Returns an Odlc JSON formatted proto.

Example Request:

GET /api/odlcs/1 HTTP/1.1
Host: 192.168.1.2:8000
Cookie: sessionid=9vepda5aorfdilwhox56zhwp8aodkxwi

Example Response:

Note: This example reformatted for readability; actual response may be entirely on one line.

HTTP/1.1 200 OK
Content-Type: application/json

{
  "id": 1,
  "mission": 1,
  "type": "STANDARD",
  "latitude": 38,
  "longitude": -76,
  "orientation": "N",
  "shape": "RECTANGLE",
  "shapeColor": "RED",
  "autonomous": false
}
POST /api/odlcs/(int:id)/image

Add or update odlc image thumbnail.

id is the unique identifier of a odlc, as returned by POST /api/odlcs. See GET /api/odlcs/(int:id) for more information about the odlc ID.

This endpoint is used to submit an image of the associated odlc. This image should be a clear, close crop of the odlc. Subsequent calls to this endpoint replace the odlc image.

The request body contains the raw binary content of the image. The image should be in either JPEG or PNG format. The request must not exceed 1 MB in size.

Example Request:

POST /api/odlcs/2/image HTTP/1.1
Host: 192.168.1.2:8000
Cookie: sessionid=9vepda5aorfdilwhox56zhwp8aodkxwi
Content-Type: image/jpeg

<binary image content ...>
```http

Example Response:

```http
HTTP/1.1 200 OK

Image uploaded.
PUT /api/odlcs/(int:id)/image

Equivalent to POST /api/odlcs/(int:id)/image.

GET /api/odlcs/(int:id)/image

Download previously uploaded odlc thumbnail. This simple endpoint returns the odlc thumbnail uploaded with a POST /api/odlcs/(int:id)/image request.

id is the unique identifier of a odlc, as returned by POST /api/odlcs. See GET /api/odlcs/(int:id) for more information about the odlc ID.

The response content is the image content itself on success.

Example Request:

GET /api/odlcs/2/image HTTP/1.1
Host: 192.168.1.2:8000
Cookie: sessionid=9vepda5aorfdilwhox56zhwp8aodkxwi

Example Response:

HTTP/1.1 200 OK
Content-Type: image/jpeg

<binary image content ...>
DELETE /api/odlcs/(int:id)/image

Delete odlc image thumbnail.

id is the unique identifier of a odlc, as returned by POST /api/odlcs.

This endpoint is used to delete the image associated with a odlc. A deleted image will not be used in scoring.

NOTE: You do not need to delete the odlc image before uploading a new image. A call to POST /api/odlcs/(int:id)/image or PUT /api/odlcs/(int:id)/image will overwrite the existing image.

Example Request:

DELETE /api/odlcs/2/image HTTP/1.1
Host: 192.168.1.2:8000
Cookie: sessionid=9vepda5aorfdilwhox56zhwp8aodkxwi

Example Response:

HTTP/1.1 200 OK

Image deleted.

Automation

This section describes how to write admin automation for the interop server by writing scripts which connect directly to the database and bypass the webserver. Note that the database and Django configurations only permit local access, so you'll need to run any such scripts locally. This may be useful while testing to automatically setup test cases (e.g. test mission) or analyze results (e.g. turning radius).

Configure Django

The first step when writing a script is to import Django and have it setup for programmatic access. Start the script with the following:

import os
import sys

# Add server code to Python PATH for imports.
sys.path.append('/path/to/server')
# Add environment variable to get Django settings file.
os.environ.setdefault("DJANGO_SETTINGS_MODULE", "server.settings")

# Setup Django.
from django.core.wsgi import get_wsgi_application
application = get_wsgi_application()

Import SUAS Code

The next step is to import the various models that you want to access. The following shows how to import the MissionConfig and GpsPosition models.

from auvsi_suas.models.gps_position import GpsPosition
from auvsi_suas.models.mission_config import MissionConfig

Read & Write Objects

The following shows how to read all MissionConfig objects and save a GpsPosition object. For details on how to perform actions like this on Django models, see the Django Tutorials.

# Print all mission objects.
print(MissionConfig.objects.all())

# Create and save a GPS position.
gpos = GpsPosition(latitudel=38.145335, longitude=-76.427512)
gpos.save()