Git Product home page Git Product logo

aavek / aeolus-ocean Goto Github PK

View Code? Open in Web Editor NEW
27.0 2.0 1.0 151 KB

An all-weather, day-and-night, collision avoidance simulator that can be implemented as a digital twin for the autonomous COLREG-compliant navigation of maritime vessels.

License: BSD 3-Clause "New" or "Revised" License

computer-vision graphics machine-learning reinforcement-learning unity3d autonomous ocean simulation boat unity

aeolus-ocean's People

Contributors

aavek avatar

Stargazers

 avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar

Watchers

 avatar  avatar

Forkers

ziqi21

aeolus-ocean's Issues

How to deploy other reinforcement learning path planning algorithms

I would like to express my gratitude for providing this remarkable platform. I am highly interested in How to deploy other reinforcement learning path planning algorithms and I'm eager to explore its capabilities on the current platform. Could you please guide me on how to access the algorithm and witness its effects? Your insights or any relevant documentation would be greatly appreciated

Regarding the Underlying algorithms used!

Hello! I would like to express my gratitude to all who worked on this project.

My team and I are tackling the same subject. I'm currently in the process of researching how Path Planning algorithms can be aligned with the rules for avoiding collisions at sea (COLREG rules) and the collaborative navigation (COLAV) standards in maritime settings. In my research, I've come across a variety of different algorithms, such as Velocity Obstacles, Evolutionary Algorithms, Deep Reinforcement Learning, Artificial Potential Fields (APF), Ant Colony Optimization (ACO), variations of RRT, and different types of A* algorithms. I'd greatly appreciate your insights into the most effective algorithms [Which are best?] for path planning and collision avoidance that adhere to COLREGs.

Furthermore, if it's feasible, I'd be extremely grateful if I could access your source code, even if it's just for the reinforcement learning component. Your assistance would be immensely valuable to me.

Thanks so much for your help!

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    ๐Ÿ–– Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. ๐Ÿ“Š๐Ÿ“ˆ๐ŸŽ‰

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google โค๏ธ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.