Example repository for autonomous behaviors using TurtleBot robots and behavior trees, as well as Docker workflows in ROS based projects.
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Updated
Jun 16, 2025 - Python
Example repository for autonomous behaviors using TurtleBot robots and behavior trees, as well as Docker workflows in ROS based projects.
ROS package which uses the Navigation Stack to autonomously explore an unknown environment with help of GMAPPING and constructs a map of the explored environment. Finally, a path planning algorithm from the Navigation stack is used in the newly generated map to reach the goal. The Gazebo simulator is used for the simulation of the Turtlebot3 Waf…
End to end motion planner using Deep Deterministic Policy Gradient (DDPG) in gazebo
Implementation of Q-learning algorithm and Feedback control for the mobile robot (turtlebot3_burger) in ROS.
In this repo we use Turtlebot 3 along with ROS 2 and Gazebo to explore an unknown csv environment, navigate through it and create a map
Benchmarking Platform for Classic and Learned Path Planning Algorithms.
This is repository for the course ROS2 Autonomous Driving and SLAM using NAV2 with TurtleBot3 on Udemy.
Autonomous Driving with TurtleBot3
A platform for executing RRT exploration in ROS Noetic and Ubuntu 20.04LTS
A ROS 2 package providing an easy-to-extend framework for and library of swarm behaviors.
2019 DGIST DPoom project under UGRP : SBC and RGB-D camera based full autonomous driving system for mobile robot with indoor SLAM
Autonomous Exploration, Mapping and Path-Planning using Octomap
Multi-robot collaborative exploration and mapping through Voronoi partition and DRL in unknown environment
Package for Path Planning and Tracking created using ROS2, Turtlebot3, A*, and PurePursuit
Pytorch implementations of the multi-agent reinforcement learning algorithms, including QMIX, VDN, COMA, MADDPG, MATD3, FACMAC and MASoftQ for path planning of swarm of mobile robots.
Machine learning based line following using TurtleBot3 with ROS2 Jazzy and Gazebo Harmonic
Implementation of A* pathfinding algorithm on a differential-drive robot
This project is mainly about testing different path planning techniques in a certain world full of obstacles and how turtlebot3 managed to get to the goal position. It tackles 3 path planning technquies which are ( Artificial potential field (APF), Breadth first search (BFS), A*).
This package implements a naive obstacle avoidance technique for Turtlebot 3 using planar laser range-finder. It has been tested using Turtlebot 3 simulation in Gazebo.
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