A novel and efficient methodology that enables the robot to maneuver safely through dense crowds in more ‘human-like’ patterns.
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Updated
Jul 26, 2024 - Jupyter Notebook
A novel and efficient methodology that enables the robot to maneuver safely through dense crowds in more ‘human-like’ patterns.
Twin Delayed DDPG
Implementation of TD3 agent in PyTorch.
Aligning an optical interferometer with beam divergence control and continuous action space.
Tests SOTA algorithms using pendulum as baseline environment
tabular and deep rl algorithms
Project for Artificial Intelligence course at University of Ljubljana, Faculty of Computer and Information science.
The pytorch implementation of td3
Develop and implement reinforcement learning for real-world navigation in DuckieTown, optimizing performance and resilience for reliable autonomous movement, backed by interpretable decision-making tools.
Deep Reinforcement Learning for mobile robot navigation in ROS2 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.
Repository contains codes for the course CS780: Deep Reinforcement Learning
Teaching an bipedal bot how to walk using a TD3 algorithm (variant of Reinforcement Learning - Actor & Critic method)
Project files of CS780: Deep Reinforcement Learning
TD3 and PPO implementation -- Final project for the course ELEC-E8125 Reinforcement Learning at Aalto University
A codebase for continuous action spaces Reinforcement Learning algorithms
Implementation of Reinforcement Learning Based Autonmous Control of a TurtleBot2 as a substitute for a Formula SAE Car
A PyTorch implementation of the DRL algorithm TD3
A Decentralized, Fully Autonomous Drone Delivery System for Reliable, Efficient Transport of Goods
A Torch Based RL Framework for Rapid Prototyping of Research Papers
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