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LIMO Open-Source Mobile Robot (ROS compatible)
AgileX Robotics | A-000000-04918
€2,371.20
20 perc. French VAT inc.
Discover LIMO, a robot based on an Agilex mobile platform. This evolutionary robotic structure is dedicated to the development of artificial intelligence. LIMO is available in 3 versions: LIMO, LIMO PRO, and LIMO ROS2.
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LIMO Mobile Robot: Everything for Your Navigation AI
The Agilex LIMO mobile robot offers an evolutionary structure and full ROS compatibility dedicated to AI development and autonomous navigation applications. This open-source mobile robot is fully programmable with open resources and is perfect for students (in robotics engineering, GEII, etc.) and for the research world. Furthermore, its compatibility with Google Assistant provides various possibilities as a service and reception robot.
It consists of an Agilex mobile platform with interchangeable wheels. You can switch between track driving, 4-wheel omnidirectional driving, differential driving, or Ackermann steering.
4 Types of Applications Available in Autonomous Navigation
The LIMO mobile robot is compatible with ROS (1 and 2) and the Gazebo simulator. This provides access to a wide range of open-access demos and sample programs for the development of your artificial intelligence.
LIMO allows you to explore various possibilities in terms of autonomous navigation:
- Mapping
- Autonomous navigation
- Obstacle avoidance and path planning
- Simultaneous Localization and Mapping (SLAM and V-SLAM)
With its built-in camera, LiDAR, and robust inertial unit, your LIMO mobile robot explores, detects, monitors, and analyzes its environment like a true sentinel. Ideal for security and surveillance applications and for creating an autonomous UGV capable of mapping all the places it traverses.
LIMO Mobile Robot: 3 Available Versions
The LIMO robotic platform comes in 3 versions: a standard, pro, and ROS2.
LIMO Mobile Robot: Standard Version
The basic version of the LIMO mobile robot includes an Nvidia Jetson Nano, an EAI X2L LiDAR, and an Orbbec DaBai depth camera.
LIMO PRO: Robotic Platform for Immersive Learning
The LIMO PRO mobile robot integrates the NVIDIA Orin Nano, an EAI T-mini Pro LiDAR, and the Orbbec Dabai depth camera. These various sensors give the robot a robust perception of its environment. It is ideal for developing applications for autonomous navigation, obstacle avoidance, and visual recognition.
LIMO PRO is an ideal robotic platform for students and researchers. Its numerous sensors and advanced software facilitate immersive learning.
LIMO PRO is compatible with ROS 1 Noetic and ROS 2 Foxy for flexible software integration. Its battery provides up to 2.5 hours of continuous use.
LIMO ROS 2: The Power of Intel NCU i7
The LIMO ROS 2 mobile robot is equipped with an Intel NCU i7 processor, allowing it to run ROS 2 on Ubuntu 22.04. This version is ideal for research and education in the field of autonomous mobile robots.
LIMO ROS 2 enables exploration of the latest capabilities of ROS 2, including key open-source frameworks such as Navigation2 for mobile robot navigation and MoveIt2 for advanced robotic arm motion planning.
LIMO ROS 2 has a long-lasting battery life of 2.5 hours. It is available with ROS 2 only (not with ROS 1).
Comparison of Different LIMO Versions
| LIMO | LIMO PRO | LIMO ROS2 | |
| Dimensions | 322*220*251mm | 322*220*251mm | 322*220*251mm |
| Weight | 4.8kg | 4.8kg | 4.8kg |
| Payload | 4kg | 4kg | 4kg |
| Ground clearance | 24mm | 24mm | 24mm |
| Steering Structure | 40 N·m | 40 N·m | 40 N·m |
| Display | 7-inch | 7-inch | 7-inch |
| IPC | Jeston Nano | Orin Nano | Intel NUC i7 |
| Depth Camera | Orbbec DaBai | Orbbec DaBai | Orbbec DaBai |
| LiDAR | EAI X2L | EAI T-mini Pro | EAI T-mini Pro |
| Battery | 5.2Ah 12V | 10Ah 12V | 10Ah 12V |
| Working Time | 1H | 2.5H | 2.5H |
| Standby Time | 2H | 4H | 4H |
| Operating System | Ubuntu 18.04 | Ubunutu 20.04 | Ubuntu 22.04 |
| ROS Version | ROS1 Melodic | ROS1 Noetic/ROS2 Foxy | ROS2 Humble |
| Control Method | Mobile App/Command Control | Mobile App/Command Control | Mobile App/Command Control |
| App Control Range | 10m | 10m | 10m |
Technical Specifications of LIMO, LIMO PRO, and LIMO ROS2 Robots
| LIMO | LIMO PRO | LIMO ROS2 | |
| Overall Dimensions | 322*220*251mm | 322*220*251mm | 322*220*251mm |
| Weight | 4.8kg | 4.8kg | 4.8kg |
| Payload | 4kg | 4kg | 4kg |
| Minimum ground clearance | 24mm | 24mm | 24mm |
| Wheel base | 200 mm | 200 mm | 200 mm |
| Tread | 175 mm | 175 mm | 175 mm |
| Drive type | Hub motor (4x14.4W) | Hub motor (4x14.4W) | Hub motor (4x14.4W) |
| No load max speed | 1 m/s | 1 m/s | 1 m/s |
| Ackermann minimum turning radius | 0,4 m | 0,4 m | 0,4 m |
| Work environment | -10°C ~ +40°C | -10°C ~ +40°C | -10°C ~ +40°C |
| Max. climbing capacity | 40° | 40° | 40° |
| Power interface | DC （5.5x2.1mm) | DC （5.5x2.1mm) | DC （5.5x2.1mm) |
| Operating System | Ubuntu 18.04 | Ubunutu 20.04 | Ubuntu 22.04 |
| IMU | MPU6050 | HI22 | HI22 |
| CPU | 6 Core Arm@ Cortex@-A78AE | i7-1135G7@2.40GHz x 8 | |
| GPU | 1024-core CUDA | Xe Graphics | |
| Battery | 5.2Ah 12V | 10Ah 12V | 10Ah 12V |
| Working time | 1H | 2.5H | 2.5H |
| Stand-by time | 2H | 4H | 4H |
| Communication interface | Wifi, Bluetooth | Wifi, Bluetooth | Wifi, Bluetooth |
| LiDAR | EAI X2L | EAI T-mini Pro | EAI T-mini Pro |
| Depth camera | Orbbec DaBai | Orbbec DaBai | Orbbec DaBai |
| IPC | Jeston Nano 4G | Jetson Orin Nano 8G | Intel NUC i7 8G |
| USB-HUB | TYPE-C x1，USB2.0 x2 | TYPE-C x1，USB2.0 x2 | TYPE-C x1，USB2.0 x2 |
| Display | 7 inch touch screen | 7 inch touch screen | 7 inch touch screen |
| ROS Version | ROS1 Melodic | ROS1 Noetic/ROS2 Foxy | ROS2 Humble |
| Control mode | Mobile APP，command control | Mobile APP，command control | Mobile APP，command control |
| Mobile APP | Bluetooth，maximum distance 10m | Bluetooth，maximum distance 10m | Bluetooth，maximum distance 10m |
Discover LIMO, a robot based on an Agilex mobile platform. This evolutionary robotic structure is dedicated to the development of artificial intelligence. LIMO is available in 3 versions: LIMO, LIMO PRO, and LIMO ROS2.
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