Implementation of the paper "Towards Optimally Decentralized Multi-Robot Collision Avoidance via Deep Reinforcement Learning"
Track and detect objects or human poses in images and videos using a user-friendly application.
Claim its page: indexed whatever its rank, translated into six languages, and enriched with what you write yourself.
Get an email alert on its next release or when it starts trending — never miss the moment.
Free · no card · unsubscribe anytimeImplementation of the paper "Towards Optimally Decentralized Multi-Robot Collision Avoidance via Deep Reinforcement Learning"
rl-collision-avoidance has 458 stars on GitHub. It has been forked 96 times. rl-collision-avoidance is written mainly in Python. It has been in active development since 2019. Its main topics are collision-avoidance, crowd-navigation, ppo, reinforcement-learning.
Implementation of the paper "Towards Optimally Decentralized Multi-Robot Collision Avoidance via Deep Reinforcement Learning"
rl-collision-avoidance is an open-source project.
Yes. rl-collision-avoidance is free and open source — you can use, modify and self-host it.
rl-collision-avoidance is written mainly in Python.
Add this live badge to your README — your GitHub stars and directory rank, refreshed daily.
[](https://olud.ai/project/acmece-rl-collision-avoidance.html)
Measured from GitHub topics shared by both projects, weighted by how rare each topic is.