Stars
一个基于 ROS 2 Humble 和 Nav2 导航栈实现的自主巡逻机器人项目。该机器人能够在一键启动仿真环境、导航系统和应用程序后，自主地在预设的地图路径点之间进行巡逻。在到达每个巡逻点后，它会自动执行拍照和中文语音播报任务。
Deep Reinforcement Learning for mobile robot navigation in ROS2 Gazebo simulator. Using DRL (SAC, TD3) neural networks, a robot learns to navigate to a random goal point in a simulated environment …
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 g…
在turtlebot3，pytorch上使用DQN,DDPG,PPO,SAC算法，在gazebo上实现仿真。Use DQN, DDPG, PPO, SAC algorithm on turtlebot3, pytorch on turtlebot3, pytorch, and realize simulation on gazebo. Use DQN, DDPG, PPO, SAC algo…
learning the weight of each paras in DWA(Dynamic Window Approach) by using DQN(Deep Q-Learning)
Motion planning(Path Planning and Trajectory Planning/Tracking) of AGV/AMR：python implementation of Dijkstra, A*, JPS, D*, LPA*, D* Lite, (Lazy)Theta*, RRT, RRT*, RRT-Connect, Informed RRT*, Vorono…
[ZJU Robotics Project] DWA and Astar algorithms for wheeled-robot path planning
Novel reinforcement learning based local planner that accounts for the dynamic constraints of the robot to enable smooth robot trajectories. Reward shaping is done to enable a spatially aware navig…
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 envir…
Using stable-baselines3 'PPO' reinforcement learning algorithm to train dynamic window approach
Deep Reinforcement Learning based autonomous navigation in realistic simulation environments.
RLGF is a general training framework suitable for UAV deep reinforcement learning tasks. And integrates multiple mainstream deep reinforcement learning algorithms(SAC, DQN, DDQN, PPO, Dueling DQN, …