RoboSense Fairy LiDAR with accessories

Name: LiDAR RoboSense Fairy| Generation Robots
Brand: RoboSense
SKU: eb1f08c9-2b28-4c93-9325-19af7e33dec7
Price: 2028 EUR
Availability: InStock

Robosense | A-000000-08045

€2,028.00 VAT incl. €1,690.00 VAT excl.

The LiDAR RoboSense Fairy is a digital LiDAR with mid-range performance for 3D perception in mobile robotics and 3D mapping.

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RoboSense Fairy: accurate, dense 3D perception, easy to integrate

Key takeaways

Compact, lightweight design (< 350 g / φ75×H70 (mm))
Ultra-high accuracy: 0.5 cm
High-density point cloud: ~685,000 pts/s (48 lines) and ~1,370,000 pts/s (96 lines)
150 m range
Integrated IMU
Ideal for 3D mapping, obstacle avoidance, and autonomous robot navigation

Overview

The RoboSense Fairy is a LiDAR designed for 3D perception in robotics, combining accurate measurements with a dense point cloud. It delivers 0.5 cm accuracy, a 360° × 32° field of view, and a range up to 150 m (including 80 m @ 10%).

Its angular resolution (0.25° (H) / 0.33° (V)) and throughput (up to ~1,370,000 pts/s) support obstacle detection, scene segmentation, and SLAM, even on thin objects. The 10 Hz frequency (adjustable) helps balance responsiveness and computing load.

For integration, it streams data over UDP via Ethernet (100Base-TX / 100Base-T1): 3D coordinates, reflectivity, and timestamp. Time synchronization (GPRMC + 1PPS, PTP, gPTP) is useful for multi-sensor systems (LiDAR, cameras, IMU).

It is well suited for embedded use thanks to < 10 W power consumption and a 9–32 V supply. It is also rugged (IP67 / IP6K9K, -40°C to +60°C) and Class 1 laser safe (940 nm) for shared test environments.

Applications and project examples

3D mapping and reconstruction: dense geometry capture to model scenes (outdoor surveying, structure reconstruction, terrain capture).
Autonomous navigation and obstacle avoidance: using the 3D cloud to detect obstacles and secure trajectories (mobile robots in shared spaces, indoor/outdoor tests).
Localization and SLAM: integration into a LiDAR localization stack, leveraging timestamps and synchronization for multi-sensor fusion.
Multi-sensor fusion: LiDAR/camera/IMU time alignment via 1PPS and PTP/gPTP (perception rigs, instrumented platforms, test benches).
Service robotics: integration on delivery robots and cleaning robots when 360° perception and point density are key.
Logistics and industrial mobility: autonomous forklifts, navigation in mixed zones, obstacle and curb detection.
Drones and lightweight systems: integration on UAVs and portable mapping devices thanks to the compact size and low weight.