Agilex LIMO ROS2 (LIMO ROS2)

Agilex LIMO ROS2 (LIMO ROS2)

The LIMO ROS2 variant is positioned as a ready-to-deploy ROS 2 system featuring an Intel NUC i7-class computing unit running Ubuntu 22.04 with ROS 2 Humble, paired with a sensor suite intended for mapping, localization, and obstacle avoidance tasks. 

Design and Features

Multi-modal chassis concept

A defining characteristic of the LIMO platform is its ability to switch between motion modes, enabling experimentation with different kinematic constraints and control strategies. The LIMO user documentation describes swift transitions between:

• Four-wheel differential mode

• Ackermann steering mode

• Tracked mode (using add-on tracks)

• Mecanum wheel mode 

This multi-modal approach is often used in robotics teaching labs to demonstrate how navigation stacks, planners, and controllers behave differently depending on the robot’s drive model.

Integrated “simulation table” workflow

AgileX describes a dedicated simulation table concept intended to simulate and test functions in controlled scenarios (e.g., miniature environments for SLAM and navigation exercises). 

Sensors and perception modules

The LIMO ROS2 product description highlights a sensor bundle centered on EAI T-mini Pro LiDAR and an Orbbec Dabai depth camera, aimed at mapping, localization, navigation planning, and dynamic obstacle avoidance. 

Technology and Specifications

Core computing and operating environment

The LIMO ROS2 configuration is marketed with an Intel NUC i7 compute platform running Ubuntu 22.04 and ROS 2 Humble, intended to provide access to open-source libraries for vision, navigation, and motion development. 

Mechanical and performance specifications

From the LIMO ROS user manual (ROS-based configuration), representative specifications include:

• Overall dimensions: 322 × 220 × 251 mm

• Dead load (robot weight): 4.8 kg

• Payload (load): 4 kg

• Max speed (no-load): 1 m/s

• Minimum turning radius (Ackermann): 0.4 m

• Max climbing capacity: 20° 

Power and battery

AgileX indicates an increased battery capacity of 10,000 mAh for the LIMO ROS2 offering, and the manual lists a 10 Ah / 12 V battery specification alongside typical working and standby times (usage-dependent). 

Sensors and I/O (typical configuration)

The manual enumerates common onboard components such as:

• LiDAR: EAI T-mini Pro

• Depth camera: Dabai

• Wireless: Wi-Fi and Bluetooth

• Interfaces: USB and HDMI (via onboard compute) 

ROS 2 software stack and open-source packages

AgileX maintains ROS 2 packages for LIMO ROS2 (Humble), including driver, bring-up/launch files, message definitions, and Gazebo simulation components. The repository structure lists packages such as limo_base, limo_bringup, limo_msgs, and a Gazebo-related package (limo_car). 

The same documentation specifies a development environment of Ubuntu 22.04 + ROS 2 Humble, with standard ROS 2 tooling for teleoperation and steering control (e.g., teleop_twist_keyboard and rqt_robot_steering). 

Applications and Use Cases

Education and robotics curriculum

LIMO ROS2 is frequently positioned for hands-on learning in:

• ROS 2 basics (nodes, topics, TF, launch, lifecycle)

• Mobile robot kinematics and control (differential vs. Ackermann vs. mecanum)

• Sensor integration (LiDAR + depth camera)

• Introductory SLAM and navigation labs 

Research and prototyping

With ROS 2 Humble and an onboard Intel NUC-class computer, the platform can serve as a testbed for:

• 2D/3D SLAM experiments

• Path planning and obstacle avoidance in indoor environments

• Vision-based behaviors (line following, object detection demos) 

Simulation-first development

Because the platform is designed to work with ROS and Gazebo, teams can prototype autonomy and control pipelines in simulation and then deploy to hardware, a common workflow in AMR development. 

Advantages / Benefits

One platform, multiple drive behaviors

By supporting four motion modes, the LIMO approach helps reduce the cost and complexity of maintaining separate robot bases for differential, Ackermann, tracked, and mecanum demonstrations. 

ROS 2–ready compute and sensors

A pre-integrated Ubuntu 22.04 + ROS 2 Humble environment with a LiDAR and depth camera can accelerate setup time for labs and pilot projects focused on navigation and perception. 

Open-source ecosystem

Vendor-supported ROS 2 packages (drivers, launch files, messages, simulation) reduce integration effort and make the platform easier to adopt for teams that want to customize autonomy stacks.

FAQ Section

What is AgileX LIMO ROS2?

AgileX LIMO ROS2 is a compact ROS 2 mobile robot development platform designed for education and research, featuring an Intel NUC i7-class computer running Ubuntu 22.04 with ROS 2 Humble. 

How does AgileX LIMO ROS2 work?

LIMO ROS2 combines a multi-modal mobile chassis with onboard compute, LiDAR, and a depth camera. Developers run ROS 2 nodes for drivers, perception, and navigation, then command the robot through teleoperation or autonomy stacks. 

Why is LIMO ROS2 important for robotics learning?

It provides a practical way to learn ROS 2, mobile robot kinematics, and autonomy workflows (SLAM, localization, planning) on a real robot, with open-source packages and common sensors used in AMR projects. 

What are the benefits of AgileX LIMO ROS2?

Key benefits include ROS 2 Humble readiness, a LiDAR + depth camera perception stack, and multi-modal mobility (including differential and Ackermann options) that supports a wide range of education and prototyping tasks. 

Summary

AgileX LIMO ROS2 is a ROS 2 Humble–based mobile robot platform built around an Intel NUC i7-class computer, LiDAR + depth sensing, and a multi-modal chassis concept that supports multiple drive behaviors. Its combination of onboard computing, open-source ROS 2 packages, and robotics-lab-friendly form factor makes it a commonly cited option for AMR education, SLAM and navigation research, and rapid prototyping of perception-driven autonomy.