Drl_grasping
Deep Reinforcement Learning for Robotic Grasping from Octrees
| Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
|---|---|---|---|---|---|---|---|---|---|---|
| Simulator | 2,029 | a year ago | 625 | other | C# | |||||
| A ROS/ROS2 Multi-robot Simulator for Autonomous Vehicles | ||||||||||
| Awesome Robotics | 817 | 3 months ago | 4 | |||||||
| A curated list of awesome links and software libraries that are useful for robots. | ||||||||||
| Gibsonenv | 814 | 3 months ago | 48 | mit | C | |||||
| Gibson Environments: Real-World Perception for Embodied Agents | ||||||||||
| Spot_mini_mini | 740 | 2 years ago | 11 | mit | C++ | |||||
| Dynamics and Domain Randomized Gait Modulation with Bezier Curves for Sim-to-Real Legged Locomotion. | ||||||||||
| Gym Gazebo | 673 | 5 years ago | n,ull | other | Python | |||||
| Refer to https://github.com/AcutronicRobotics/gym-gazebo2 for the new version | ||||||||||
| Drl Robot Navigation | 214 | 8 months ago | 16 | mit | Python | |||||
| Deep Reinforcement Learning for mobile robot navigation in ROS Gazebo simulator. Using Twin Delayed Deep Deterministic Policy Gradient (TD3) neural network, a robot learns to navigate to a random goal point in a simulated environment while avoiding obstacles. | ||||||||||
| Drl_grasping | 196 | a year ago | 4 | bsd-3-clause | Python | |||||
| Deep Reinforcement Learning for Robotic Grasping from Octrees | ||||||||||
| Gym Gazebo2 | 193 | 5 years ago | apache-2.0 | Python | ||||||
| gym-gazebo2 is a toolkit for developing and comparing reinforcement learning algorithms using ROS 2 and Gazebo | ||||||||||
| Rl Quadcopter | 130 | 2 years ago | 3 | Jupyter Notebook | ||||||
| Teach a Quadcopter How to Fly! | ||||||||||
| Overcoming Exploration From Demos | 117 | 2 years ago | 3 | mit | Python | |||||
| Implementation of the paper "Overcoming Exploration in Reinforcement Learning with Demonstrations" Nair et al. over the HER baselines from OpenAI | ||||||||||
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