S-RL Toolbox: Reinforcement Learning (RL) and State Representation Learning (SRL) for Robotics
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Updated
Apr 5, 2021 - Python
S-RL Toolbox: Reinforcement Learning (RL) and State Representation Learning (SRL) for Robotics
Train deep reinforcement learning model for robotics grasping. Choose from different perception layers raw Depth, RGBD and autoencoder. Test the learned models in different scenes and object datasets
Files used in the development of a digital twin for a robot cell at NTNU with the use of Visual Components 4.0 and OPC UA
Scalable cross-platform multi-control framework for KUKA LBR iiwa cobots (Python - ROS - ROS2)
Kuka Reacher Reinforcement Learning Sim2Real Environment for Omniverse Isaac Gym/Sim
Using principles of forward and inverse kinematics to perform pick and place operations using a serial manipulator in simulation
Train Soft Actor-Critic model for KukaDiverseObject environment in pybullet
ROS2 support for KUKA youBot [WIP]
Control KUKA Manipulator to follow a predefined trajectory using Jacobain approach and Inverse Kinematic approach
Manipulator dynamic symbolic model extraction (Euler-Lagrange method) + identification of manipulator dynamics with trajectory optimization
ME 604- Robotics Project (IIT Bombay) Kuka Robot
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