Tortoisebot
TortoiseBot is an extremely learner-friendly and cost-efficient ROS-based Open-sourced Mobile Robot that is capable of doing Teleoperation, Manual as well as Autonomous Mapping, Navigation, Simulation, etc.
Install / Use
/learn @rigbetellabs/TortoisebotREADME
Tortoisebot ROS2 Humble Release
<p align="center"><a href="#connect-with-us-">Connect with Us</a> • <a href="#1-installation">Installation</a> • <a href="#2-setup">Setup</a> • <a href="#3-demos">Demos</a> <h1 align="center"> TortoiseBot </h1>
Connect with us 
<a href="https://rigbetellabs.com/"></a>
<a href="https://rigbetellabs.com/discord">
</a>
<a href="https://www.youtube.com/channel/UCfIX89y8OvDIbEFZAAciHEA">
</a>
<a href="https://www.instagram.com/rigbetellabs/">
</a>
1. Installation
1.1 Required Dependences:
sudo apt install ros-humble-joint-state-publisher ros-humble-robot-state-publisher ros-humble-cartographer ros-humble-cartographer-ros ros-humble-gazebo-plugins ros-humble-teleop-twist-keyboard ros-humble-teleop-twist-joy ros-humble-xacro ros-humble-nav2* ros-humble-urdf
cd ~/your workscpace
colcon build
1.2 Clone this repo
Make sure you clone the repo in your robot and your remote PC
git clone -b ros2-humble https://github.com/rigbetellabs/tortoisebot.git
cd ~/your workscpace
colcon build
2. Setup
- Run bringup.launch.py to only spawn the robot
- Run autobringup.launch.py to spawn the robot with navigation and slam/localization
- Launch the files with use_sim_time:=False when working on real robot
2.1 Launching the robot
ros2 launch tortoisebot_bringup autobringup.launch.py use_sim_time:=True exploration:=True
- exploration:=False for passed a saved map to navigation
2.2 Launch files for reference
SLAM
- cartographer.launch.py
Navigation
- navigation.launch.py
Rviz
- rviz.launch.py
Gazebo
- gazebo.launch.py
2.3 Remote PC
While performing colcon build on remote-pc please add the below to ignore ydlidar_sdk, ydlidar_ros2_driver, v4l2_camera since lidar will not be connected to remote-pc.
colcon build --packages-ignore ydlidar_sdk ydlidar_ros2_driver v4l2_camera
3. Demos
<!-- Simulation | Visualisation of Sensors (Lidar, Odometery, Camera) :-------------------------:|:-------------------------:  | Teleop | Mapping | Navigation :-------------------------:|:-------------------------:|:-------------------------:  |  |  -->The TortoiseBot 🐢🤖
The ReadMe is divided into several sections as per different topics and is constantly been updated and maintained with new updates by our talented and dedicated 👥 Team at RigBetel Labs LLP. So don't forget to often come here and check on it for the latest and greatest software updates, projects & skills for your TortoiseBot. Also don't forget to 🌟 Star this repository on top-right corner of the screen to show your 💖 Love and Support 🤗 for our Team. 🤩 It will make us happy and encourage us to make and bring more such projects for you. 😍 Click here to get started.
Join our community for Free. Post your projects or ask questions if you need any help.
TortosieBot is sourced, assembled, made & maintained by our team 🧑🏻🤝🧑🏻 at<br>
RigBetel Labs LLP®, Charholi Bk., via. Loheagaon, Pune - 412105, MH, India 🇮🇳<br> 🌐 RigBetelLabs.com 📞 +91-8432152998 📨 getintouch.rbl@gmail.com , info@rigbetellabs.com <br> LinkedIn | Instagram | Facebook | Twitter | YouTube | Discord Community
Related Skills
mcp-shrimp-task-manager
2.1kShrimp Task Manager is a task tool built for AI Agents, emphasizing chain-of-thought, reflection, and style consistency. It converts natural language into structured dev tasks with dependency tracking and iterative refinement, enabling agent-like developer behavior in reasoning AI systems.
mcp-shrimp-task-manager
2.1kShrimp Task Manager is a task tool built for AI Agents, emphasizing chain-of-thought, reflection, and style consistency. It converts natural language into structured dev tasks with dependency tracking and iterative refinement, enabling agent-like developer behavior in reasoning AI systems.
contextplus
1.5kSemantic Intelligence for Large-Scale Engineering. Context+ is an MCP server designed for developers who demand 99% accuracy. By combining RAG, Tree-sitter AST, Spectral Clustering, and Obsidian-style linking, Context+ turns a massive codebase into a searchable, hierarchical feature graph.
Peekaboo
2.9kPeekaboo is a macOS CLI & optional MCP server that enables AI agents to capture screenshots of applications, or the entire system, with optional visual question answering through local or remote AI models.

