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LSR200Auto ROS 2 Autoware Autonomous Driving Platform
- 100% Open-Source Code
- Professional Technical Support
- Comprehensive Development Resources
- For bulk orders, institutional procurement, or corporate purchasing, please contact us for a formal quotation and procurement support.
The LSR200Auto is an open-source autonomous driving research platform for ROS, Autoware, outdoor mapping, localization, perception, planning, and vehicle-control development. Available in Ackermann and 4WD configurations, it combines NVIDIA Jetson computing with multi-line LiDAR, RTK GNSS, depth vision, inertial sensing, radar, wheel odometry, and optional autonomous recharging for universities, research institutes, and autonomous-system developers.
- Ackermann Lite, Ackermann Pro, Ackermann Ultra, and 4WD Ultra configurations
- Autoware development workflows for localization, mapping, perception, mission planning, motion planning, and vehicle control
- ROS 2 Autoware.Universe on Ultra configurations; ROS 1 / ROS 2 resources also provided for broader robotics development
- 16-line mechanical LiDAR, RTK GNSS, H30 9-axis IMU, depth camera, and MR20 77 GHz mmWave radar in the autonomous-driving sensor stack
- Outdoor 3D reconstruction, NDT localization initialization, multi-point navigation, and point-cloud perception workflows
- Optional autonomous charging / docking
- Fully open development resources including source code, robot models, schematics, manuals, and ROS tutorials
Product Overview
LSR200Auto is designed for low-speed autonomous-driving and advanced mobile-robot research where a complete perception-to-control development chain is required. The platform supports Autoware-based workflows together with conventional ROS SLAM, Nav2, visual perception, target tracking, autonomous exploration, and secondary development.
The LSR200Auto family spans compact Ackermann research vehicles through a higher-payload four-wheel-drive platform. Researchers can select a configuration based on turning geometry, payload, terrain requirements, onboard compute, and whether autonomous charging is needed.
Configuration Comparison
| Parameter | Ackermann Lite | Ackermann Pro / Ultra | 4WD Ultra |
|---|---|---|---|
| Max Speed | 1.3 m/s | 1.65 m/s | 2.1 m/s |
| Rated Payload | 25 kg | 35 kg | 60 kg |
| Net Weight | 11.5 kg | 48 kg | 48.5 kg |
| Max Climbing Angle | 27° | 11° | 28° |
| Single-Step Clearance | 30 mm | 75 mm | 60 mm |
| Default Dimensions | 443.7 × 348.1 × 433.5 mm | 882.9 × 766 × 569 mm | 650 × 650 × 539.8 mm |
| Minimum Turning Radius | 0.8 m | 1.78 m | 0 m |
| Suspension | Oscillating axle | 4-wheel independent | 4-wheel independent |
| Battery | 24 V 6000 mAh LiFePO4 | 24 V 20000 mAh LiFePO4 | 24 V 20000 mAh LiFePO4 |
| Approx. Battery Life | 6 h | 9 h | 10.5 h |
| Wheel Encoder | 500-line GMR AB encoder | 500-line GMR AB encoder | 4096-line magnetic encoder |
Autoware Autonomous Driving Stack
The platform supports Autoware development across the core autonomous-driving pipeline: localization, mapping, object detection and tracking, mission planning, motion planning, and vehicle control. Ultra configurations support ROS 2 Autoware.Universe, while the Pro configuration also supports ROS 1 Autoware.AI.
Development examples include sequential multi-point navigation through Autoware.Universe and GNSS-assisted initial positioning for NDT map matching.
Perception & Localization Sensor Stack
16-Line Mechanical LiDAR
The C16 mechanical LiDAR uses pulsed TOF ranging with 16 channels, 360° horizontal field of view, 30° vertical field of view, selectable 5 / 10 / 20 Hz frame rates, and selectable 70–150 m ranging. Typical ranging accuracy is ±1 cm, and the enclosure is rated IP67.
G70 RTK GNSS
The G70 GNSS module can receive RTK correction data through a 4G-connected base-station or correction-service workflow. Positioning accuracy is 1.5 m for single-point positioning and 1 cm + 1 ppm for RTK. The positioning update rate is configurable from 1–20 Hz, with a default of 1 Hz; for typical operation, an update rate at or below 5 Hz is recommended.
H30 9-Axis IMU
The H30 integrates a 3-axis gyroscope, 3-axis accelerometer, and 3-axis magnetometer for attitude and motion sensing. It supports raw inertial and navigation data output up to 400 Hz; the standard shipping configuration is 200 Hz. Reserved interfaces include UART, I2C, and RS485.
Depth Camera, Radar & Ultrasonic Sensing
The autonomous-driving sensor suite also includes a depth camera and MR20 77 GHz millimeter-wave radar for perception research. A six-sensor ultrasonic array—four front and two rear—helps cover close-range blind spots outside the LiDAR scanning plane. The ultrasonic array is standard on the 4WD model and optional on applicable Ackermann configurations.
ROS, SLAM & AI Development Resources
Beyond Autoware, open-source development resources include RTAB-Map 3D mapping, 2D LiDAR SLAM, ORB-SLAM2, Nav2, YOLO object detection, depth-based visual following, KCF tracking, AR-tag recognition, RRT autonomous exploration, web camera monitoring, RGB line following, LiDAR following, LiDAR angle masking, TEB / DWA path planning, DWB / MPPI / RPP controller examples, coverage planning, chassis-kinematics analysis, path recording and playback, URDF models, mobile control tools, Bluetooth code flashing, and LLM integration workflows.
Autonomous Recharging
Auto-recharging is available as a selectable option. Using ROS mapping and navigation, the charging-station position can be calibrated in the map so the robot can return and dock when required. Development tutorials cover charging-station calibration, docking methods, and low-battery return logic.
Applications
Autonomous Driving Research
Use the LSR200Auto for Autoware algorithm development, localization, mapping, perception, planning, control, multi-sensor fusion, and low-speed autonomous vehicle research.
Outdoor Mapping & Inspection
The LiDAR, RTK GNSS, IMU, depth vision, and optional charging workflow support research in campus patrol, outdoor inspection, mapping, delivery, and long-duration autonomous operation.
Education & Secondary Development
Open source code, robot models, schematics, development manuals, system images, and tutorials make the platform suitable for university teaching, postgraduate research, and algorithm validation.
Need Help Selecting?
For the inertial sensor used in this platform, see the H30 9-axis ROS IMU. For standalone high-precision outdoor localization options, compare the G70 / G90 GNSS RTK modules. For a smaller indoor differential platform, see the LSR100 service robot platform, or browse the Research Robot Platforms collection.
Key Features
LSR200Auto combines Autoware, outdoor localization, multi-sensor perception, vehicle-control hardware, and a fully open ROS development stack. Feature availability depends on the selected Ackermann / 4WD version and optional equipment.
01 Autoware Autonomous Driving System
The platform supports a complete Autoware development workflow covering localization, mapping, object detection and tracking, mission planning, motion planning, and vehicle control for autonomous-driving research.
02 Advanced 3D Reconstruction Algorithms
Supports full 3D scene reconstruction with multiple example workflows for large-scale outdoor mapping and autonomous-system research.
03 G70 Differential Positioning RTK Module
The G70 GNSS module can receive RTK correction data through a 4G-connected base-station or correction-service workflow. It can provide high-precision outdoor positioning and can be used to initialize or reset localization when LiDAR map matching has drifted.
| Feature | Details |
|---|---|
| Output Level | TTL / RS232 |
| Output Protocol | NMEA-0183 / RTCM / UBLOX |
| Initialization Time | Hot start < 5 s; cold start < 30 s |
| GNSS Antenna Interface | 1 × MCX |
| Position Update Rate | 1–20 Hz; default 1 Hz; recommended ≤5 Hz |
| Positioning Accuracy | Single point: 1.5 m; RTK: 1 cm + 1 ppm |
| Velocity Accuracy | 0.05 m/s |
| Operating Voltage / Current | 5 V / 0.5 A |
| Dimensions / Weight | 54.5 × 46.5 × 13.2 mm / 36 g |
04 High-Performance 4G DUT
The 4G communication unit provides a cellular link for RTK correction data and other remote communication workflows. Carrier-band compatibility should be confirmed for the deployment country.
| Feature | Details |
|---|---|
| Operating Temperature | -40°C to 85°C |
| Serial Data Interface | RS232 |
| Power | 100 mA @ 12 V |
| Antenna Interface | 50 Ω / SMA female |
| Supported Networks | 2G / 3G / 4G adaptive; CAT1 |
| LTE Bands | FDD B1/B3/B5/B8; TDD B34/B38/B39/B40/B41 |
| SIM | Micro SIM; SIM/USIM 1.8 V / 3 V |
| Serial Parameters | 115200 baud, 8 data bits, no parity, 1 stop bit |
05 H30 High-Precision 9-Axis Attitude Sensor
The H30 integrates a 3-axis MEMS gyroscope, 3-axis accelerometer, and 3-axis magnetometer for attitude, acceleration, angular-rate, and magnetic-field measurements. A high-performance attitude-fusion and sensor-compensation pipeline is used for navigation output.
| Feature | Details |
|---|---|
| Reserved Interfaces | UART / I2C / RS485 |
| Dimensions | 60 × 46 × 11.7 mm |
| Input Voltage | 4.5–5.2 V DC |
| Output Interface | Type-C / pin header |
| Axes | 9-axis |
| Power Consumption | 165 mW |
| Operating Temperature | -40°C to 85°C |
| Command Configuration | Calibration, parameter configuration, mode switching |
| Raw IMU Output | Temperature, acceleration, angular velocity, magnetic field; up to 400 Hz |
| Navigation Output | Yaw / pitch / roll, quaternion, timestamp; up to 400 Hz |
| Default Shipping Frequency | 200 Hz |
06 High-Precision Motion Sensing
Ackermann configurations use a 500-line AB-phase GMR encoder for improved wheel-speed and low-speed odometry resolution during precise maneuvering.
| Feature | Details |
|---|---|
| Motor Model | MD36L P27 |
| Motor Voltage | 24 V DC |
| Rated Power | 60 W |
| No-load Speed | 310 ± 12% rpm |
| Rated Speed | 260 ± 12% rpm |
| Rated Torque | 10 kg·cm |
| Stall Torque | 64 kg·cm minimum |
| No-load Current | 0.4 A maximum |
| Rated Current | 2.9 A maximum |
| Stall Current | 22.1 A maximum |
07 Outdoor Navigation & LiDAR Perception
The 16-line mechanical LiDAR uses TOF ranging and provides 360° horizontal perception for outdoor mapping and autonomous-driving research. The C16 provides typical ranging accuracy of ±1 cm.
08 Autonomous Power Management
Optional autonomous charging supports return-to-station and docking workflows based on ROS mapping and navigation. Tutorials cover charging-station calibration, docking methods, and low-battery return logic.
09 3D Ultrasonic Blind-Spot Detection System
A six-sensor ultrasonic array with four front-facing and two rear-facing sensors helps cover close-range blind spots outside the LiDAR scanning plane and reduce collision risk in tight spaces. The array is standard on the 4WD model and optional on applicable Ackermann configurations.
Fully Open-Source ROS Development Library
The development library includes the following software examples and resources for robotics research. Availability and performance depend on the selected controller, sensors, ROS version and optional hardware.
1. RTAB-Map 3D VSLAM & LiDAR Integration
Supports RTAB-Map vision-only mapping and LiDAR–vision fusion mapping for 3D environment reconstruction in ROS 1 and ROS 2.
2. Classic 2D LiDAR Mapping & Navigation
ROS 2 resources include Gmapping, Cartographer and slam_toolbox. ROS 1 resources include Gmapping, Hector, Karto and Cartographer. Navigation examples cover point-to-point navigation, multi-point waypoints and dynamic obstacle avoidance.
3. ORB-SLAM2 Visual Mapping
Includes ORB-SLAM2 for real-time camera pose estimation and sparse 3D reconstruction, with metric-scale depth information available in RGB-D mode.
4. ROS Qt Graphical User Interface
A Qt-based ROS interface provides convenient launch controls and real-time feedback such as robot velocity, battery status and system health.
5. YOLO Object Detection
ROS 1 resources include YOLOv3 workflows, while ROS 2 resources include YOLOv8 and YOLO11 workflows for object detection and custom-model experiments.
6. LLM Deployment
Supports development workflows for offline local or cloud-connected large-language-model integration. Practical model size and latency depend on the selected onboard computer and software stack.
7. Depth-Based Visual Following
Uses depth-camera information to estimate target distance and bearing for visual-following experiments.
8. KCF Target Tracking
Includes Kernelized Correlation Filter tracking resources for identifying and tracking targets with stable visual features.
9. AR Tag Recognition & Following
Supports 6-DOF AR-tag pose detection for tag-following behaviors and tag-based localization experiments.
10. RRT Autonomous Exploration
Includes an RRT-based workflow for autonomous exploration, mapping, map saving and return-to-start experiments.
11. Web-Based Camera Monitoring
Provides browser-based access to the robot camera stream for remote monitoring and development tasks.
12. RGB Camera Line Following
Supports RGB-vision line following with LiDAR-assisted obstacle avoidance for line-following research.
13. LiDAR-Based Following
Uses LiDAR scans for nearby-target selection and following experiments.
14. LiDAR Angle Masking
SDK-based LiDAR angle masking allows selected scan sectors to be filtered according to the sensor and application configuration.
15. TTS Interaction
Includes text-to-speech interaction workflows and support for extending online voice-dialogue functions with compatible voice services.
16. TEB & DWA Path Planning
Includes video tutorials and Python-based exercises for learning TEB and DWA navigation and local path-planning methods.
17. DWB / MPPI / RPP Controllers
Provides DWB, MPPI and Regulated Pure Pursuit controller examples for different navigation scenarios and robot footprints.
18. Full Coverage Path Planning
Supports generation of coverage paths for user-defined areas, useful for cleaning, inspection and systematic-area traversal research.
19. Chassis Kinematics Analysis
Development resources include kinematic-analysis examples for Ackermann, differential, tracked, Mecanum, omnidirectional and 4WD chassis types.
20. Path Recording & Playback
Manual trajectories can be recorded and replayed autonomously using Nav2-based workflows.
21. Comprehensive URDF Models
Includes URDF models for simulation, visualization and robot-software development based on the physical platform geometry.
22. ROS Mobile App for Navigation
A mobile application is provided for supported ROS motion-control, mapping and navigation workflows.
23. Hardware Tuning & Parameter App
Android and iOS tools support real-time parameter tuning, gravity-sensing control and waveform visualization for supported hardware functions.
24. Wireless Code Flashing
A Bluetooth module supports remote debugging and wireless code-flashing workflows for supported low-level controller development.
25. 3D Reconstruction for Autonomous-Driving Research
Multi-line LiDAR enables outdoor 3D mapping, environment reconstruction and point-cloud perception research.
26. Autoware.Universe Multi-Point Navigation
Pre-configured Autoware.Universe examples use sequential waypoint commands to demonstrate continuous multi-point autonomous navigation.
27. GNSS Initial Positioning for NDT Matching
Latitude and longitude data from the GNSS system can be used to set an initial vehicle pose or help reset localization when LiDAR map matching has deviated significantly.
Frequently Asked Questions
What is the LSR200Auto designed for?
LSR200Auto is designed for autonomous-driving research, Autoware development, ROS navigation, outdoor mapping, multi-sensor perception, localization, planning, control, and university or laboratory research.
Which chassis configurations are available?
The LSR200Auto is available in Ackermann Lite, Ackermann Pro, Ackermann Ultra, and 4WD Ultra configurations. Each can be selected with or without the available auto-recharging option.
Does LSR200Auto support Autoware?
Yes. The development resources cover the Autoware pipeline including localization, mapping, perception, mission planning, motion planning and vehicle control. ROS 2 Autoware.Universe on Ultra configurations and also list ROS 1 Autoware.AI resources for a Pro configuration.
What sensors are used for autonomous-driving research?
The sensor stack includes a 16-line mechanical LiDAR, G70 RTK GNSS, H30 9-axis IMU, depth camera, MR20 77 GHz millimeter-wave radar, wheel encoders, and—on the 4WD model—six ultrasonic sensors as standard.
What positioning accuracy does the G70 RTK module provide?
positioning accuracy is 1.5 m for single-point positioning and 1 cm + 1 ppm in RTK mode.
What is the G70 positioning update rate?
The positioning update rate is configurable from 1 to 20 Hz. The default is 1 Hz, and for typical operation an update rate at or below 5 Hz is recommended.
What is the H30 IMU output rate?
The H30 supports raw inertial and navigation data output up to 400 Hz. The standard shipping setting is 200 Hz.
Does the platform support outdoor 3D mapping?
Yes. The 16-line LiDAR, RTK GNSS, IMU and provided software resources support outdoor 3D reconstruction, point-cloud processing, localization and autonomous-navigation research.
Does it support automatic charging?
Yes, auto-recharging is available as a selectable option. The associated development resources cover charging-station calibration, return-to-station logic and autonomous docking.
Are ultrasonic sensors included?
The six-sensor ultrasonic array is standard on the 4WD model. It is optional on applicable Ackermann configurations.
What are the maximum speed and payload?
Ackermann Lite reaches up to 1.3 m/s with 25 kg rated payload; Ackermann Pro / Ultra at up to 1.65 m/s with 35 kg rated payload; and 4WD Ultra at up to 2.1 m/s with 60 kg rated payload.
What open-source software resources are provided?
Development resources include Autoware examples, ROS SLAM and navigation, RTAB-Map, ORB-SLAM2, Nav2 controllers, YOLO, tracking, autonomous exploration, URDF models, path planning, path recording, mobile control tools and additional secondary-development examples.
Can I use GNSS to initialize NDT localization?
Yes. The provided workflow uses GNSS latitude and longitude data to set the vehicle's initial pose or help reset localization when LiDAR map matching has deviated significantly.
Does the platform support AI and computer vision development?
Yes. The development resources include YOLO object detection, RGB-D visual following, KCF tracking, AR-tag recognition, LLM integration and other perception workflows. Performance depends on the selected Jetson controller and software configuration.
Can I modify the platform for my own research?
Yes. LSR200Auto is intended as an open research platform. Source code, robot models, schematics, manuals and tutorials are provided to support secondary development, subject to the hardware interfaces and selected configuration.
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