LIMO PRO
ROS 2 Mobile Robot Platform

LIMO PRO
ROS 2 Mobile Robot Platform

One reconfigurable mobile robot that switches between Ackermann steering, differential drive, Mecanum-wheel, and tracked mobility for ROS education and algorithm validation.

Core Performance Metrics

4

Motion Mode

4.8kg

Payload

4hours

Runtime

45°

Max Climb (Track Mode)

Four Motion Modes, One Customizable Platform

Supports interchangeable mobility configurations, including Ackermann steering, differential drive, Mecanum wheels, and tracked mobility.

Integrated AI Computing and Perception System

Integrated NVIDIA Jetson Orin Nano, an EAI T-mini Pro LiDAR, Orbbec DaBai depth camera, and HI226 IMU provide an onboard foundation for real-time mapping, perception, object recognition, and autonomous robot development.

Open ROS Environment, From SLAM to Navigation

LIMO PRO provides ROS resources, C++ and Python interfaces, source code, simulation models, and hands-on tutorials. Developers can develop localization, obstacle avoidance, route planning, and autonomous inspection workflows with ROS navigation tools.

Who is Using LIMO PRO

Built for robotics education, autonomous-driving research, AI algorithm development, and rapid mobile robot prototyping.

Universities & Robotics Labs

For ROS education, mobile robot research, kinematics experiments, and autonomous-navigation development.

Robotics and AI Educators

For teaching Python, C++, SLAM, perception, path planning, and robot-control fundamentals through hands-on projects.

Student Competition Teams

For robotics competitions, capstone projects, and rapid prototyping that require adaptable mobility and onboard perception.

Developers & Product Prototyping Teams

For validating mobile robot algorithms, sensor configurations, and application concepts before custom hardware development.

Complete Ecosystem

Seamless integration with industry-standard hardware and software.

Components & Accessories

Configure LIMO PRO with multiple mobility modes and scenario-based training arenas.

Tracks
Tracks
Mecanum Wheels
Mecanum Wheels
Onboard Computing
Onboard Computing
Sand Table
Sand Table

Software & Algorithms

Develop with ROS, SDKs, simulation tools, and resources for SLAM, navigation, perception, and robot control.

ROS 1 / ROS 2

Phython & C++ SDK

Gmapping / Cartographer / RTAB-Map

DWA / TEB Navigation

FAQ

LIMO PRO is a four-mode ROS robot development platform for education, research, and mobile robotics prototyping. It supports Ackermann, differential, Mecanum-wheel, and tracked motion configurations.

LIMO PRO is an open, reconfigurable platform focused on mobile-robot learning and development. Its standard configuration does not include a robotic arm. LIMO COBOT is a more integrated ROS 2 mobile manipulation platform that combines the mobile base, 6-DoF arm, perception hardware, and ready-to-use grasping workflows.

Users can develop SLAM, autonomous navigation, obstacle avoidance, visual recognition, line following, voice interaction, AI inference, and optional mobile-manipulation applications.

LIMO PRO supports commonly used ROS navigation and mapping algorithms, including Gmapping, Cartographer, RTAB-Map, AMCL localization, DWA local planning, and TEB local planning. With its onboard LiDAR, depth camera, IMU, and Jetson computing, developers can build and evaluate laser SLAM, visual SLAM, autonomous navigation, obstacle avoidance, and multi-point patrol applications.

Use Ackermann mode for car-like steering, differential drive for standard indoor mobile robotics, Mecanum mode for omnidirectional movement, and tracked mode for improved terrain adaptability.

Technical Specifications

dimensions (mm)

322*220*251

weight

4.8kg

Max climb (Track Mode)

45°

runtime

4hours

LiDAR

2DLiDAR

Depth Camera

Orbbec DaBai

Onboard PC

Orin Nano

Obstacle Clearance

24mm

Tell Us Your Needs

Connect with our robotics experts to discuss your needs and discover the perfect robotics platform for your business.

ADDRESS

Head Office: XbotPark, Songshan Lake, Dongguan
Sales & Marketing: iPark, Nanshan District, Shenzhen

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