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deepbots
A wrapper framework for Reinforcement Learning in the Webots robot simulator using Python 3.
Hello folks! We are happy to inform you that a month ago deepbots had its 1.0 release.
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Our deepbots-tutorials repository has also been updated for the 1.0 release, and we have a new obstacle avoidance example in the works for our deepworlds examples repository. Feel free to check them out! Any feedback and/or contributions are more than welcome.
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deepworlds
Examples and use cases using the deepbots framework (https://github.com/aidudezzz/deepbots) with the Webots robot simulator.
Our deepbots-tutorials repository has also been updated for the 1.0 release, and we have a new obstacle avoidance example in the works for our deepworlds examples repository. Feel free to check them out! Any feedback and/or contributions are more than welcome.
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Deepbots is an open-source framework facilitating reinforcement learning in Webots. Webots provides easy-to-use tools to create your own worlds/robots, and deepbots interfaces Webots with any gym-compatible RL agent. It does this by guiding even the most novice users to create gym-style environments that are compatible with Webots (we have recreated the classic control problem CartPole successfully in Webots, among others). Deepbots handles all low-level details to interface the environment with the simulator.