DFRobot
SLAMTEC Aurora AI 3D Mapping & 6DOF Positioning Sensor
· MPN: DFR1220
The SLAMTEC Aurora is an all-in-one perception sensor for autonomous robots, combining LiDAR, binocular vision, inertial sensing and onboard AI processing in...
The SLAMTEC Aurora is an all-in-one perception sensor for autonomous robots, combining LiDAR, binocular vision, inertial sensing and onboard AI processing in a single mapping and localisation unit. It is designed to produce high-precision 3D maps and stable 6DOF positioning data without the usual complexity of building a multi-sensor fusion stack from scratch.
Inside the unit are 2D LiDAR, binocular fisheye global-shutter cameras, a 6DOF IMU and a dedicated AI processor. SLAMTEC’s neural network models are used to extract meaningful environmental features, helping the system maintain positioning through rapid movement, rotation, repetitive scenes and feature-poor areas.
Aurora outputs rich 3D point cloud data while also synchronising a high-precision top-down 2D laser grid map, making it useful for teams moving from 2D navigation workflows into 3D robotics. It is suited to humanoid robots, robotic dogs, AMRs, inspection drones, autonomous utility vehicles, large-scale surveying and GPS-denied navigation.
The package includes the SLAMTEC Aurora Positioning Mapping Sensor, a Type-C to DC5.5*2.1 PD cable, power adapter and triangular bracket. Documentation and development resources include a user manual, datasheet, ROS2 SDK, 2D mechanical drawings, 3D model and access to the SLAMTEC download resources.
Features:
- All-in-one perception system integrating LiDAR, binocular cameras, IMU, and AI processor
- Real-time 3D mapping with full 6DOF localization
- AI-based environmental feature extraction for stable positioning
- Supports extremely large-scale mapping environments
- Simultaneous 3D point cloud and 2D laser grid map output
- Stable localization during rapid motion and rotation
- Multiple connectivity interfaces including USB-C, Ethernet, and Wi-Fi
- Compact and lightweight design for robotic integration
- Global relocalization and map continuation supported
- Compatible with modern robotics development platforms and SLAM frameworks
Specifications:
- Power Input: DC 12V @ 2A (via DC5.5*2.1mm)
- Power Consumption: 10W
- LiDAR Range: 40m @ 70% Reflectivity
- 2D Map Resolution: 2cm / 5cm / 10cm (Adjustable)
- Maximum Map Area: >1,000,000 m²
- Relocalization: Global Relocation Supported
- Map Continuation: Supported
- Data Interfaces: USB-C, Ethernet (RJ45), Wi-Fi
- Positioning Mode: LiDAR + Vision + Inertial Fusion (SLAM)
- Camera: Binocular Fisheye Global Shutter, HDR, FOV 180°, 6cm Baseline
- Camera Frame Rate: 10Hz
- Weight: 505g
- Operating Temperature: 0°C to 40°C
- Max Tilt Angle: No hard requirement (Recommend ＜30° for optimal 2D mapping)
Use it when your robot needs integrated mapping, localisation and perception data with USB-C, Ethernet or Wi-Fi connectivity and ROS2 development support.
Jargon buster
Plain-language definitions for the technical terms used above.
- GPS
- The US satellite navigation system used by GNSS receivers to calculate position and time. Support for GPS is important because it is widely available and often used together with other constellations for more reliable positioning.
- IMU
- An Inertial Measurement Unit combines motion sensors to measure movement and orientation. It matters for asset tracking because it can detect movement, tilt, vibration, or changes in direction.
- LiDAR
- A sensing method that uses laser light to measure distance and build a 3D picture of the surroundings. It matters for robotics and autonomous systems because LiDAR data can help with mapping, navigation and obstacle detection.
- RJ45
- The common plug and socket style used for wired Ethernet network cables. If a board has an RJ45 connector, you can usually plug it into standard Ethernet cabling without making a custom connector.
- USB-C
- A modern reversible USB connector used for power and data connections. On this product it matters because it can connect directly to a computer as well as to a microcontroller project.
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Sensors & Input
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