Yahboom ROSMASTER M1 ROS2 Robot for SLAM & AI, Mecanum Drive, Jetson Nano/Orin Nano SUPER/RPi 5/RDK X5
Yahboom ROSMASTER M1 ROS2 Robot for SLAM & AI, Mecanum Drive, Jetson Nano/Orin Nano SUPER/RPi 5/RDK X5
Yahboom
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Overview
Yahboom ROSMASTER M1 is an AI large model ROS2 robot for robotics education, ROS research, and AI multimodal interaction experiments. It uses a Mecanum wheel chassis for 360° omnidirectional movement (lateral, diagonal, in-place rotation) and supports ROS2 HUMBLE on multiple master-control platforms including Raspberry Pi 5, RDK X5, Jetson Nano 4GB, Jetson Orin Nano 8G, and also lists Jetson Orin Nano SUPER and Jetson Nano B01.
The robot integrates multimodal perception hardware (3D depth camera, 2MP HD camera PTZ, TOF LiDAR, and an AI large model voice module) to support SLAM mapping/navigation, visual recognition, path planning, and multimodal interaction. It adopts a dual-model inference architecture with a decision layer (task understanding/planning) and an execution layer (action generation/response), and supports dialogue interruption, dynamic feedback reasoning, and optional expansion with a RAG knowledge base.
Key Features
- Mecanum omnidirectional drive chassis with 360° omnidirectional movement
- High-torque 520 encoder metal motors (x4)
- Multi-master platform compatibility: Raspberry Pi 5, RDK X5, Jetson Nano 4GB, Jetson Orin Nano 8G (also listed: Jetson Orin Nano SUPER, Jetson Nano B01)
- ROS2 HUMBLE compatible
- Multi-sensor fusion perception: 3D depth camera, 2MP HD camera PTZ, TOF LiDAR, AI large model voice module + speaker
- Multimodal large model capabilities: scalable RAG knowledge base, visual large language model, text large-scale language model, bimodal reasoning architecture, dynamic feedback reasoning
- LiDAR precise perception: 360° omnidirectional perception, dynamic obstacle avoidance, fixed-point navigation, mapping navigation, path planning, road network planning
- 3D depth vision functions: depth distance/height/volume calculation, 3D real-world mapping, deep edge detection, 3D point cloud recognition
- AI vision stack listed: MediaPipe, OpenCV, YOLOv11
- Learning resources: detailed courses and codes; tutorials and video tutorials with English subtitles
Specifications
| Model | ROSMASTER M1 |
| Robot type | AI large model ROS2 robot (mecanum-wheel mobile robot) |
| ROS version | ROS2 HUMBLE |
| Chassis | Mecanum wheel chassis |
| Motors | 520 high-torque encoder metal motor x4 |
| Cameras | 2MP HD camera PTZ; 3D depth camera (also listed as “2MP HD camera/depth camera”) |
| LiDAR | TOF high-performance LiDAR |
| Voice | AI large model voice module + speaker |
| Battery pack | 12V 6000mAh high-capacity battery pack |
| Storage | 128GB / 256GB |
| Body | All-aluminum alloy body |
| Master control platforms (listed) | Raspberry Pi 5; RDK X5; Jetson Nano 4GB; Jetson Orin Nano 8G; Jetson Orin Nano SUPER; Jetson Nano B01 |
| Dimensions | 284.4 x 231.4 x 181.4 mm |
Applications
- SLAM mapping and navigation; SLAM intelligent multi-point navigation; SLAM map object search
- AI visual recognition and visual interaction; scene understanding
- Path planning; fixed-point navigation; dynamic obstacle avoidance
- Voice interaction and intent inference; multimodal interaction experiments
- Visual tracking/following; line tracking (“autonomous cruise”)
- Multi-robot synchronous motion control (as listed)
Function notes: Road network planning is listed as not supported on Raspberry Pi and Jetson Nano B01 versions. Track-map road sign recognition / track-map navigation functions are listed as requiring a separate track map, and Raspberry Pi versions are listed as not supporting these track-map functions.
For pre-sales compatibility checks (master control platform, storage option, and function support), contact support@rcdrone.top or visit https://rcdrone.top/.
Manuals
Tutorials
Yahboom ROSMASTER M1 Tutorials
Videos
Details
ROSMASTER M1 is a ROS2 HUMBLE mobile robot built for AI and robotics education with 360° mecanum-wheel mobility.
Multimodal perception (camera, depth, LiDAR, and voice) supports SLAM mapping, navigation, and interactive experiments.
A quick feature map of the platform’s core capabilities: multimodal reasoning, LiDAR navigation, depth vision, and AI vision tools.
Designed for ROS developers who want an embodied-intelligence robot that’s easy to teach, test, and extend.
A two-layer pipeline separates task understanding from action execution, with dynamic feedback and interruption support.
Platform options and learning materials are outlined to help choose the right configuration for your lab or classroom.
Run LLM-style tasks such as Q&A, text generation, voice interaction, and visual understanding workflows.
Visual prompts can be used for scene understanding and object tracking in interactive robotics projects.
Depth data can be combined with vision to answer distance questions and support track-map driving features where available.
Track-map accessories can be added for road-sign recognition and related autonomous driving activities.
Color line tracking enables autonomous cruising along marked routes for classroom demos and robotics exercises.
SLAM mapping and multi-point navigation workflows support planning routes across multiple target locations.
Voice intent and map context can be used for object search tasks and higher-level navigation routines.
Higher-level behaviors combine perception and navigation to break down longer tasks into actionable steps.
Context-aware responses help the robot adapt to changing goals, with optional track-map driving activities.
Course modules cover a wide range of AI + ROS learning topics, with code resources organized by function.
Choose between kit versions based on your preferred master-control platform and sensor configuration.
Controller performance guidance helps match compute needs to your ROS2 and multimodal inference workload.
The ROSMASTER M1’s LiDAR functions cover common ROS mapping options, navigation modes, and obstacle-avoidance features with IMU-assisted fusion.
Depth camera support enables point cloud depth data, distance measurement, RTAB-Map 3D visual mapping navigation, volume measurement, and edge detection.
Built-in YOLOv11 vision examples cover image segmentation, pose estimation, image classification, and object detection for robotics tasks.
The ROSMASTER M1 supports OpenCV and MediaPipe workflows for tasks like gesture, skeleton, fingertip tracking, 3D detection, and color recognition.
The ROSMASTER M1 supports AI visual interaction features such as gesture control, line and color tracking, face tracking, and object following.
The Yahboom ROSMASTER M1 ROS2 setup supports multi-robot navigation, synchronized control from a single host, and formation driving.
The Yahboom ROSMASTER M1 supports scenario-based autonomous driving practice in ROS, with a note that the Raspberry Pi version does not support this function.
ROSMASTER M1 supports road sign detection, lane keeping, autonomous parking, and steering decisions based on lane markings and traffic lights.
The ROSMASTER M1 aluminum-alloy chassis uses four Mecanum wheels to support 360° omnidirectional movement, including lateral and diagonal travel.
Yahboom ROSMASTER M1 is developed using the ROS2 system and references the ROS2 Humble Hawksbill version.
ROSMASTER M1 supports RViz simulation for visualizing radar and odometry data, camera feeds, map building, and SLAM planning.
The ROSMASTER M1 integrates a top-mounted LiDAR for 360° scanning to support mapping and navigation tasks.
The ROSMASTER M1 supports cross-platform control via a computer terminal, a mapping/navigation mobile app, or a standard USB wireless controller.
The ROSMASTER M1 robot layout includes lidar, an optional PTZ camera and ROS master, plus a USB 3.0 hub and 6000mAh battery pack for clean integration.
The 3D structured light depth camera kit connects over USB Type‑C and supports a 0.2–4 m working distance with up to a 73.8° horizontal field of view for mapping and navigation projects.
The Standard/Superior Kit includes a T-MINI Plus TOF LiDAR (5V, 300mA) with 0.05–12m ranging and 0–360° scanning.
The Yahboom ROSMASTER M1 voice module pairs dual MEMS microphones with a compact speaker and USB Type‑C interface for 5V voice input and playback.
The Yahboom ROSMASTER M1 ROS2 robot control board uses a Type‑C DC 12V power input and provides DC 12V/5V outputs for driving motors and peripherals.
The ROSMASTER M1 uses a 12.6V 6000mAh lithium-ion battery pack with built-in protection features and a compact pack size for easy installation.
The ROSMASTER M1 course syllabus outlines lessons from setup and PID calibration to vision tasks like QR recognition, lane detection, and color tracking.
The Yahboom ROSMASTER M1 ROS2 robot supports LiDAR mapping and navigation functions alongside chassis and voice-control options for development and testing.
The ROSMASTER M1 ROS2 robot package includes a structured curriculum covering YOLOv11 development, ROS2 basics, Linux, Docker, and image processing topics.
Yahboom ROSMASTER M1 ROS2 tutorials and code resources are organized into folders for AI model basics, development, and vision courses.
The ROSMASTER M1 learning materials cover LiDAR mapping and navigation, mobile app control, AI tutorials, and ROS2 basics with English subtitles.
Yahboom ROSMASTER M1 includes accompanying video tutorials, a 3D model file download, and access to technical support resources.
ROSMASTER series specs are compared across key areas like chassis type, RGBD camera options, display, control board, and battery capacity.
ROSMASTER M1 uses a mecanum-wheel chassis with 80mm wheels, four 520 geared motors (1:56), and optional T-MINI PLUS or SLAM C1 LiDAR support.
The ROSMASTER platform pairs a mecanum wheel chassis and 520 geared motors with options like RGBD/depth camera selection, LiDAR, and a 12.6V 6000mAh battery.
ROSMASTER M3 Pro features an 80mm mecanum-wheel chassis, 4× 520 geared motors (1:56), dual LiDAR, and a 6-DOF robotic arm, with control board options including Raspberry Pi 5 and Jetson.
ROSMASTER M1 ROS2 robot specifications list overall dimensions along with system, storage, and power details for planning integration.
The ROSMASTER M1 kit includes the robot chassis, control board with OLED, encoder motors with mecanum wheels, battery pack, charger, and essential cables and tools.
The ROSMASTER M1 accessory set includes a T-MINI PLUS LiDAR, camera options, Type-C cables, mounting brackets, and screw packs for assembly.
The ROSMASTER M1 ROS2 robot accessory list includes optional Jetson or Raspberry Pi boards, cooling parts, power/data cables, and 128GB/256GB storage options.
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