Nexo PyCozmo

Note: This project is a fork and continuation of the original PyCozmo library. It has been updated, maintained, and modernized to ensure full compatibility with recent Python versions (3.13, 3.14, and above).

Nexo PyCozmo is a pure-Python communication library, alternative SDK, and application for the Cozmo robot . It allows controlling a Cozmo robot directly, without having to go through a mobile device, running the Cozmo app.

The library is loosely based on the Anki Cozmo Python SDK and the cozmoclad ("C-Like Abstract Data") library.

This project is a tool for exploring the hardware and software of the Digital Dream Labs (originally Anki) Cozmo robot. It is unstable and heavily under development.

Usage

Basic:

import time
import pycozmo

with pycozmo.connect() as cli:
    cli.set_head_angle(angle=0.6)
    time.sleep(1)

Advanced:

import pycozmo

cli = pycozmo.Client()
cli.start()
cli.connect()
cli.wait_for_robot()

cli.drive_wheels(lwheel_speed=50.0, rwheel_speed=50.0, duration=2.0)

cli.disconnect()
cli.stop()

Documentation

https://pycozmo.readthedocs.io/

Robot Support

Sensors:

• Camera
• Cliff sensor
• Accelerometers
• Gyro
• Battery voltage
• Cube battery voltage
• Cube accelerometers
• Backpack button (v1.5 hardware and newer)

Actuators:

• Wheel motors
• Head motor
• Lift motor
• OLED display
• Speaker
• Backpack LEDs
• IR LED
• Cube LEDs
• Platform LEDs (when available)

On-board functions (see docs/functions.md for details:

• Wi-Fi AP
• Bluetooth LE
• Localization
• Path tracking
• NV RAM storage
• Over-the-air (OTA) firmware updates

Off-board functions (see docs/offboard_functions.md for details:

• Procedural face generation
• Cozmo animations from FlatBuffers .bin files
• Personality engine - work in progress
• Cozmo behaviors - work in progress
• Motion detection
• Object (cube and platform) detection
• Cube marker recognition
• Face detection
• Face recognition
• Facial expression estimation
• Pet detection
• Camera calibration
• Navigation map building
• Text-to-speech
• Songs

Extra off-board functions:

• Vector animations from FlatBuffers .bin files
• Vector behaviors
• ArUco marker recognition
• Cozmo and Vector robot detection
• Drivable area estimation
• Voice commands

If you have ideas for other functionality share them via GitHub.

Tools

• pycozmo_app.py - an alternative Cozmo application, implementing off-board functions (video).
• pycozmo_dump.py - a command-line application that can read and annotate Cozmo communication from pcap files or capture it live using pypcap.
• pycozmo_replay.py - a basic command-line application that can replay .pcap files back to Cozmo.
• pycozmo_anim.py - a tool for examining and manipulating animation files.
• pycozmo_update.py - a tool for over-the-air (OTA) updates of Cozmo's firmware.
• pycozmo_protocol_generator.py - a tool for generating Cozmo protocol encoder code.

Note: PyCozmo and pycozmo_protocol_generator.py in particular could be used as a base for creating a Cozmo protocol encoder code generator for languages other than Python (C/C++, Java, etc.).

Examples

Basic:

• minimal.py - minimal code to communicate with Cozmo, using PyCozmo
• extremes.py - demonstrates Cozmo lift and head control
• backpack_lights.py - demonstrates Cozmo backpack LED control
• display_image.py - demonstrates visualization of image files on Cozmo's display
• events.py - demonstrates event handling
• camera.py - demonstrates capturing a camera image
• go_to_pose.py - demonstrates moving to a specific pose (position and orientation)
• path.py - demonstrates following a predefined path

Advanced:

• display_lines.py - demonstrates 2D graphics, using PIL.ImageDraw on Cozmo's display (video)
• rc.py - turns Cozmo into an RC tank that can be driven with an XBox 360 Wireless controller or Logitech Gamepad F310
• video.py - demonstrates visualizing video captured from the camera back on display
• cube_lights.py - demonstrates cube connection and LED control
• cube_light_animation.py - demonstrates cube LED animation control
• charger_lights.py - demonstrates Cozmo charging platform LED control
• audio.py - demonstrates 22 kHz, 16-bit, mono WAVE file playback through Cozmo's speaker
• nvram.py - demonstrates reading data from Cozmo's NVRAM (non-volatile memory)
• procedural_face.py - demonstrates drawing a procedural face on Cozmo's display
• procedural_face_show.py - demonstrates generating a procedural face
• procedural_face_expressions.py - demonstrates displaying various facial expressions (video)
• anim.py - demonstrates animating Cozmo

PyCozmo In The Wild

• Expressive Eyes - rendering various facial expressions using PyCozmo's procedural_face module
• an application that recognizes ArUco markers, using OpenCV
• a ROS2 driver
• another ROS2 driver

Connecting to Cozmo over Wi-Fi

A Wi-Fi connection needs to be established with Cozmo before using PyCozmo applications.

1. Wake up Cozmo by placing it on the charging platform
2. Make Cozmo display it's Wi-Fi PSK by rising and lowering its lift
3. Scan for Cozmo's Wi-Fi SSID (depends on the OS)
4. Connect using Cozmo's Wi-Fi PSK (depends on the OS)

This video summarizes the connection process.

PyCozmo vs. the Cozmo SDK

A Cozmo SDK application (aka "game") acts as a client to the Cozmo app (aka "engine") that runs on a mobile device. The low-level communication happens over USB and is handled by the cozmoclad library.

In contrast, an application using PyCozmo basically replaces the Cozmo app and acts as the "engine". PyCozmo handles the low-level UDP communication with Cozmo.

+------------------+                   +------------------+                   +------------------+
|     SDK app      |     Cozmo SDK     |    Cozmo app     |       Cozmo       |      Cozmo       |
|      "game"      |     cozmoclad     |     "engine"     |      protocol     |     "robot"      |
|                  | ----------------> |   Wi-Fi client   | ----------------> |     Wi-Fi AP     |
|                  |        USB        |    UDP client    |     UDP/Wi-Fi     |    UDP Server    |
+------------------+                   +------------------+                   +------------------+

Requirements

• Python 3.13 or newer
• Pillow 10.3.0 - Python image library
• FlatBuffers - serialization library
• dpkt - TCP/IP packet parsing library

Installation

Using pip:

pip install --user nexo-pycozmo

pycozmo_resources.py download

From source:

git clone https://github.com/nexo-robot/nexo-pycozmo.git
cd pycozmo
python setup.py install --user

pycozmo_resources.py download

From source, for development:

git clone https://github.com/nexo-robot/nexo-pycozmo.git
cd pycozmo
python setup.py develop --user
pip install --user -r requirements-dev.txt

pycozmo_resources.py download

Support

Bug reports and changes should be sent via GitHub:

https://github.com/nexo-robot/nexo-pycozmo

Disclaimer

This project is not affiliated with Digital Dream Labs or Anki.