Yahboom ROSMASTER A1 ROS2 Robot Car with Ackerman Steering Chassis, TOF LiDAR, PTZ Camera, Voice AI

Overview

ROSMASTER A1 is a ROS2 robot car platform (ROS2 HUMBLE) developed for ROS education and artificial intelligence research. It adopts an Ackerman motion/steering chassis to replicate real vehicle steering characteristics, and integrates AI large model voice interaction plus visual perception for SLAM mapping and navigation, environment understanding, and multimodal (voice/vision/text) interaction.

It supports multiple master control options including Raspberry Pi 5 (8GB), RDK X5 (8GB), Jetson Nano B01 (4GB), and Jetson Orin Nano SUPER (8GB). Typical hardware options include an AI large model voice module, 2MP HD camera PTZ (standard kit), 3D depth camera PTZ (superior/ultimate kits), and TOF LiDAR (including T-mini Plus LiDAR or SLAM C1 LiDAR depending on version).

Key Features

• Ackerman steering chassis for vehicle-like motion: aluminum alloy Ackerman chassis; turning geometry with different inner/outer wheel angles.
• Chassis hardware for precise control: equipped with a 20kg metal digital servo for precise steering; high-torque 520 encoder motor; 68mm non-slip rubber tire; high-precision bearing.
• Multimodal large model capabilities: scalable RAG knowledge base; visual large language model; text large-scale language model; bimodal reasoning architecture; dynamic feedback reasoning.
• Built-in three AI large models (as described):
  • Large language model: real-time connection to a large model platform for text command understanding and flexible responses.
  • Voice large model: AI large model voice module and speaker supporting real-time conversion between voice and text (“listen” and “speak”).
  • Visual large model: depth camera or HD camera for image understanding, object identification, and text/voice feedback output.
• 3D depth vision (optional): depth distance; volume measurement; 3D point cloud recognition; 3D real-world mapping; deep edge detection.
• TOF LiDAR functions: road network planning; mapping navigation; path planning; dynamic obstacle avoidance; multi-point navigation; 360° omnidirectional perception.
• ROS2 development ecosystem: compatible with Gazebo and RViz; supports SLAM mapping and navigation, obstacle avoidance, tracking, and visual recognition functions.
• AI vision software stack (as listed): Mediapipe, OpenCV, YOLOv11.

Specifications

Version Configurations (Differences)

ROS Robot Configuration Selection Suggestions (as listed)

It is strongly recommended to choose the configuration of Jetson Orin Nano SUPER board to ensure the smoothness of large model operation and the effect of function realization. (Label shown: “Computing power increased by 70%”.)

Summary text shown: ROSMASTER A1 supports Raspberry Pi, RDK X5 and Jetson series master control, and the usage methods are basically the same. Different master control only affects the performance of the car. The course materials, product function, control software are consistent.

Functional Case Test Comparison (Superior Kit)

ROS Functions (Highlights)

• LiDAR functions: high-precision TOF LiDAR integrated with encoder and IMU gyroscope data for mapping and navigation; supports multiple mapping algorithms and single-point/multi-point navigation; controllable via the app; optimized repositioning and navigation to reduce positioning drift and improve stability and reliability.
• Supported mapping/navigation components (as shown): Gmapping LiDAR mapping; Cartographer LiDAR mapping; slam_toolbox LiDAR mapping; IMU dual LiDAR fusion filtering; TEB path planning dynamic obstacle avoidance; APP mapping navigation; repositioning mapping navigation.
• Road network planning: labeled as NEW and shown as “Just for Jetson ORIN NANO version”.
• Depth camera functions (Only for Superior Kit/Ultimate Kit): 3D structured light depth camera outputs depth images and point cloud data; supports distance and volume measurement; can be combined with LiDAR to construct high-precision 3D color maps for improved perception and navigation. Examples shown include RTAB-Map 3D visual mapping navigation, wood block volume measurement, and edge detection.

Function Notes / Limitations (as stated)

• Autonomous driving: Raspberry Pi version not support this function.
• Road network planning: Raspberry Pi and Jetson NANO 4GB version not support this function.
• SLAM track map navigation / track map application: shown with the note “Need purchase track map by yourself”; track map is not included.
• Deep distance Q&A: marked “Only for Superior Kit”.

Applications

• ROS2 teaching, classroom labs, and robotics curriculum projects
• SLAM mapping and navigation experiments (Gazebo/RViz workflow)
• Autonomous vehicle algorithm verification on an Ackerman steering chassis (path planning, trajectory tracking, steering control)
• Machine vision projects: object detection and tracking, visual recognition, and visual/voice interaction
• Multi-point navigation and road-network style route management (supported on specific master control configurations as noted)

For pre-sales configuration guidance (Standard/Superior/Ultimate kit selection) or integration help with ROS2 HUMBLE, contact support@rcdrone.top or visit https://rcdrone.top/.

Manuals

Tutorial link: ROSMASTER A1

Videos

Details

ROSMASTER A1 is a ROS2 Humble Ackerman robot car platform built for SLAM, navigation, and embodied AI research.

Multimodal interaction combines voice commands with visual perception for hands-free navigation tasks.

Expandable hardware options add depth vision and TOF LiDAR to support mapping, obstacle avoidance, and perception.

Choose a kit configuration based on the compute platform and sensors needed for your ROS2 workload.

Connect to large-model services and integrate voice, text, and vision workflows for embodied intelligence projects.

Three modes—text, voice, and vision—support richer human-robot interaction and task understanding.

A vehicle-like Ackerman steering geometry pairs with a high-torque servo and encoder motor for precise control.

Ackerman steering helps replicate real car behavior for lane tracking and control algorithm verification.

Example autonomy tasks include sign detection, lane keeping, parking behaviors, and route decision logic.

Road-network planning supports structured navigation routes for track-style environments and waypoint travel.

Higher-level use cases blend perception and dialogue for interactive demos, tracking, and question answering.

SLAM workflows cover mapping, multi-point navigation, and map-based search for indoor autonomy experiments.

Advanced behaviors build on environment understanding and command interpretation to execute navigation goals.

Controller guidance helps match compute performance and interfaces to your sensor stack and ROS2 features.

LiDAR mapping and depth sensing enable 2D/3D perception, distance measurement, and navigation planning.

A computer-vision toolkit supports object detection, recognition tasks, and interactive vision-based behaviors.

ROS2 Humble compatibility and RViz simulation support faster development, testing, and visualization.

360° LiDAR perception improves mapping reliability and obstacle awareness in dynamic environments.

The ROSMASTER A1 supports cross-platform remote control through an iOS/Android mapping app, a computer interface, or a standard USB wireless controller.

ROSMASTER A1 uses a layered chassis with a 6000mAh battery pack, USB 3.0 hub expansion, and optional LiDAR or camera modules for flexible builds.

Yahboom ROSMASTER A1 supports a 2MP PTZ HD camera with 360° horizontal and 180° vertical rotation or a 3D structured light depth camera with a 0.2–4 m range.

The Yahboom ROSMASTER A1 ROS2 robot integrates a TOF LiDAR on top and an AI voice module with microphone and speaker for navigation and voice interaction.

The ROSMASTER A1 ROS2 robot kit pairs a ROS robot control board with a 12.6V 6000mAh Li-ion battery pack for powering the build.

The ROSMASTER A1 course outline lays out step-by-step ROS2 learning topics, from setup and basic control to mapping and navigation.

Open-source code and step-by-step tutorial folders help you get started with ROS2 setup, programming, and demos.

The ROSMASTER A1 learning resources cover depth camera vision, LiDAR setup, mapping/track expansion, and ROS2 basics in organized tutorial modules.

Yahboom ROSMASTER A1 includes practical video tutorials, downloadable 3D model files, and after-sales technical support to help with setup and learning.

ROSMASTER A1 uses an Ackermann steering chassis with 65 mm rubber wheels and supports RGBD camera and onboard computer options such as Raspberry Pi 5 or Jetson.

ROSMASTER A1 configuration options cover mecanum chassis hardware, RGBD camera and LiDAR selections, controller boards, and battery details.

ROSMASTER A1 supports a mecanum-wheel chassis with optional RGBD camera, LiDAR, and multiple control board choices including Raspberry Pi and Jetson.

The ROSMASTER robot platform combines a mecanum-wheel chassis with options like an RGBD camera and LiDAR mapping modules for ROS2 development.

ROSMASTER A1 specifications outline key details such as system version options, storage, battery working time, interfaces, and overall dimensions.

The ROSMASTER A1 kit includes the robot car chassis plus key accessories like the control expansion board, OLED display, encoder motors, battery, wireless handle, and connection cables for setup.

ROSMASTER A1 accessory bundles list included LiDAR options, camera modules, adapter boards, mounting brackets, cables, and screw packs for different versions.