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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Deep Reinforcement Learning for mobile robot navigation in IR-SIM simulation. Using DRL (SAC, TD3, PPO, DDPG) neural networks, a robot learns to navigate to a random goal point in a simulated environment while avoiding obstacles.
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| 2026-07-31 | 327 |
| 2026-08-01 | 327 |
| 2026-08-02 | 327 |
| 2026-08-06 | 327 |
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[](https://deepwiki.com/reiniscimurs/DRL-robot-navigation-IR-SIM) **DRL Robot navigation in IR-SIM** Deep Reinforcement Learning algorithm implementation for simulated robot navigation in IR-SIM. Using 2D laser sensor data and information about the goal point a robot learns to navigate to a specified point in the environment.  **Installation** * Package versioning is managed with poetry \ `pip install poetry` * Clone the repository \ `git clone https://github.com/reiniscimurs/DRL-robot-navigation.git` * Navigate to the cloned location and install using poetry \ `poetry install` **Training the model** * Run the training by executing the train.py file \ `poetry run python robot_nav/rl_train.py` * To open tensorbord, in a new terminal execute \ `tensorboard --logdir runs` **Sources** | Package | Description | Source | |:--------|:-------------------------------------------------------------:|------------------------------------:| | IR-SIM | Light-weight robot simulator | https://github.com/hanruihua/ir-sim | | PythonRobotics | Python code collection of robotics algorithms (Path planning) | https://github.com/AtsushiSakai/PythonRobotics | **Models** | Model | Description | Model Source | |:-----------------|:-----------------------------------------------------------------------------------------------:|----------------------------------------------------------:| | TD3 | Twin Delayed Deep Deterministic Policy Gradient model | https://github.com/reiniscimurs/DRL-Robot-Navigation-ROS2 | | SAC | Soft Actor-Critic model | https://github.com/denisyarats/pytorch_sac | | PPO | Proximal Policy Optimization model | https://github.com/nikhilbarhate99/PPO-PyTorch | | DDPG | Deep Deterministic Policy Gradient model | Updated from TD3 | | CNNTD3 | TD3 model with 1D CNN encoding of laser state | - | | RCPG | Recurrent Convolution Policy Gradient - adding recurrence layers (lstm/gru/rnn) to CNNTD3 model | - | | MARL: TD3-G2ANet | G2ANet attention encoder for TD3 model in MARL setting | G2ANet adapted from https://github.com/starry-sky6688/MARL-Algorithms | | MARL: TD3-IGS | In-Graph Softmax attention model for TD3 model in MARL setting | - | **Max Upper Bound Models** Models that support the additional loss of Q values exceeding the maximal possible Q value in the episode. Q values that exceed this upper bound are used to calculate a loss for the model. This helps to control the overestimation of Q values in off-policy actor-critic networks. To enable max upper bound loss set `use_max_bound = True` when initializing a model. | Model | |:-------| | TD3 | | DDPG | | CNNTD3 | **MARL Models** Multi agent RL setting with training multiple robots a the same time with a single policy. Implementation does not use sensor informaition and only exchanged graph messages are used for navigation. Read more bout the In-Graph Softmax for MARL implemen
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matched fp:07dfe3dbd1cd6311, llm:Repository description and topics: 'Deep Reinforcement Learning for mobile robot navigation in IR-SIM simulation. Using DRL (SAC, TD3, PPO, DDPG) neural networks...'; topics include drl, ddpg, ppo, sac, td3, robot-navigation, obstacle-avoidance, ir-sim.
matched fp:07dfe3dbd1cd6311, llm:Repository description and topics: 'Deep Reinforcement Learning for mobile robot navigation in IR-SIM simulation. Using DRL (SAC, TD3, PPO, DDPG) neural networks...'; topics include drl, ddpg, ppo, sac, td3, robot-navigation, obstacle-avoidance, ir-sim.