stanley | An autonomous drone to follow a person , using the OAK-D

by Matchstic Python Version: Current License: GPL-3.0

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kandi X-RAY | stanley Summary

stanley is a Python library. stanley has no bugs, it has no vulnerabilities, it has a Strong Copyleft License and it has low support. However stanley build file is not available. You can download it from GitHub.

This is the source for my autonomous drone project, Stanley. It makes use of the OAK-D Lite for detecting people with depth (TinyYOLO v4), and then uses a subsumption architecture to send control signals via MAVLink to a drone to follow the closest person. The full project is intended to run on an NVIDIA Jetson Nano, but should work on any platform that can talk via MAVLink, and can run depthai.

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Support

stanley has a low active ecosystem.

It has 21 star(s) with 6 fork(s). There are 4 watchers for this library.

It had no major release in the last 6 months.

stanley has no issues reported. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of stanley is current.

Quality

stanley has no bugs reported.

Security

stanley has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

stanley is licensed under the GPL-3.0 License. This license is Strong Copyleft.

Strong Copyleft licenses enforce sharing, and you can use them when creating open source projects.

Reuse

stanley releases are not available. You will need to build from source code and install.

stanley has no build file. You will be need to create the build yourself to build the component from source.

Installation instructions, examples and code snippets are available.

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stanley Key Features

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stanley Examples and Code Snippets

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Community Discussions

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Vulnerabilities

No vulnerabilities reported

Install stanley

I went through the process here to setup my own drone: https://docs.luxonis.com/en/latest/pages/tutorials/first_steps/.
run ./setup.sh to install dependencies
python utils/camera.py is for debugging Yolo detections and FPS
./integration.sh to run SITL integration tests
python sitl.py to run virtualised SITL mode with direct person control
cd visualiser && yarn serve to run the SITL frontend
python src/main.py to run the full system - see the help it logs with -h
The base image for the Jetson Nano likely has Python 3.6 installed, but this code requires 3.9+. To install this new runtime, do the following:. Now, you can go through the steps to install DepthAI on the Nano. You should follow the steps specifically for the Jetson family here: https://docs.luxonis.com/projects/api/en/v2.2.1.0/install/#ubuntu.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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