Page Comparison

SIC

SIC is a framework for quickly getting started with social robotics by making it simple to combine complex devices such as Nao’s and powerful services such as Google Dialogflow.

Getting started with SIC consists of a few basic steps:

1. Installing SIC on your device

2. Installing SIC on your robot

3. Starting Redis and SIC on your device

4. Starting SIC on your robot

5. Start your program to control the robot

Installation

You can find the instructions on how to install the framework here: Install.

Setup

Once installed to all devices you want to use, we can start the framework.

This consists of two (or three) steps:

1. Start Redis

2. (Optional) Start a service, such as face detection

3. Run your program

Starting Redis on your laptop

To enable communication between all your devices, we have to start Redis on some device.

This can be done in two ways: By starting redis yourself or using docker.

In a (WSL) terminal, start redis using

# in the `framework` folder:

redis-server conf/redis/redis.conf

cd your/path/to/framework
docker compose up redis

Optionally, you can now start other services on your laptop, such as text to speech, by starting the service in a terminal. For example:

cd framework/sic_framework/services/text2speech
python3 text2speech_service.py

or with docker

docker compose up text2speech

Running a demo

To start a demo, for example to show pepper’s camera output on your screen, simply execute a python script. Some demos are available in the framework/sic_framework/tests folder.

For example, to show the This guide assumes you already followed the steps here Getting started.

For example, to show the camera feed of the robot:

...

To start the camera demo from the terminal, use the following commands.Note: This demo requires you to have the OpenCV module installed, as well as have the framework installed.

...

it might take some time to start the demo file if the SIC has never been installed on the robot.

Ubuntu / Debian / macOS

# Activate the same virtual environment where you pip installed 
# social-interaction-cloud in the installation steps
source venv_sic/bin/activate

# Go to sic_applications and the demo script
cd sic_applications/demos
python demo_nao_camera.py

Windows

# Activate the same virtual environment where you pip installed 
# social-interaction-cloud in the installation steps
.\.venv_sic\Scripts\activate

# Go to sic_applications and the demo script
cd sic_applications\demos
python demo_nao_camera.py

And, you should get the following output:

Starting SIC on /data/home/nao/.venv_sic/lib/python2.7/site-packages/sic_framework/devices/nao with redis ip 192.168.2.6
[SICComponentManager 192.168.2.7]: INFO:  - NaoqiSpeakerComponent
[SICComponentManager 192.168.2.7]: INFO:  - NaoqiButtonSensor
[SICComponentManager 192.168.2.7]: INFO:  - NaoqiAutonomousActuator
[SICComponentManager 192.168.2.7]: INFO:  - NaoqiMicrophoneSensor
[SICComponentManager 192.168.2.7]: INFO:  - NaoqiMotionActuator

...

[SICComponentManager 192.168.2.7]: INFO:  - NaoqiBottomCameraSensor
[SICComponentManager 192.168.2.7]: INFO:  - NaoqiStiffnessActuator
[SICComponentManager 192.168.2.7]: INFO:  - NaoqiMotionRecorderActuator
[SICComponentManager 192.168.2.7]: INFO:  - NaoqiTextToSpeechActuator
[SICComponentManager 192.168.2.7]: INFO:  - NaoqiTrackerActuator
[SICComponentManager 192.168.2.7]: INFO:  - NaoqiTopCameraSensor
[SICComponentManager 192.168.2.7]: INFO:  - NaoqiLookAtComponent

If all goes well, a display should pop up showing you the camera output of your robot!

API

The goal of SIC is to provide easy to use high level access to devices and services. For example, to make a NAO robot say something, run the following python script on your laptop! To see more functionality check out the framework/sic_frameworkapplications /testsdemos folder!

from sic_framework.devices import Nao
from sic_framework.devices.common_naoqi.naoqi_text_to_speech import NaoqiTextToSpeechRequest

nao = Nao(ip='192.168.0.151') # adjust this to the IP adress of your robot.

nao.tts.request(NaoqiTextToSpeechRequest("Hello!"))