1. Introduction
The Yahboom ROSMASTER R2 AI Robot Kit, specifically the ULT Version with Orin Nano Super 8GB, is an advanced educational robot designed for mechanical engineers and enthusiasts. It features an Ackerman steering structure, AI voice control, SLAM (Simultaneous Localization and Mapping), and AI vision for mapping and navigation. This manual provides detailed instructions for setting up, operating, and maintaining your robot.
2. What's in the Box
Verify that all components are present before beginning assembly.
- Car body
- Wheels
- Depth camera
- Sensor Expansion board
- 6000mAh 12V battery pack
- Charger
- ROS robot expansion board
- ROS master control (Jetson Orin Nano Super 8GB)
- Lidar (Optional: SLAM A1M8 lidar or YDLIDAR 4ROS lidar)
- AI voice interaction module (Optional)
- 7-inch display screen (Optional)
- USB wireless handle (Optional)
- 256G SSD (Optional)
- Various cables and small parts
- Screwdriver
Image: Overview of the components included in the Yahboom ROSMASTER R2 AI Robot Kit.
3. Key Features
- Ackerman Steering Structure: Utilizes a competition-level Ackerman steering design for enhanced maneuverability and performance during turns.
- ROS2 Operating System: Built on the Robot Operating System (ROS2) for robust control and advanced functionalities.
- High-Performance Hardware: Equipped with a lidar, depth camera, and voice interaction module for comprehensive sensing and interaction.
- Advanced AI Capabilities: Supports SLAM, mapping, navigation, obstacle avoidance, human body feature recognition, and voice interactive control.
- Multi-Platform Control: Can be controlled via mobile phone APP, game handle, ROS system, or computer keyboard.
- Educational Focus: Provides an exploration model for learning algorithms, AI visual recognition, autonomous driving, and 3D object recognition.
Image: The Yahboom ROSMASTER R2 robot car, highlighting its depth camera and lidar components.
4. Product Structure
The ROSMASTER R2 robot is composed of several key modules. Understanding their placement and function is crucial for assembly and operation.
Image: An exploded diagram illustrating the main structural components of the ROSMASTER R2 robot, including the lidar, depth camera, AI voice module, ROS robot expansion board, battery, and Ackerman steering chassis.
4.1 Main Components
- Lidar: Used for environmental scanning and mapping.
- Depth Camera: Provides visual data for AI vision, object recognition, and 3D mapping.
- AI Voice Interaction Module: Enables voice control and interactive commands.
- ROS Robot Expansion Board: Central control board for connecting various sensors and actuators.
- ROS Master Control: The main processing unit (e.g., Jetson Orin Nano Super 8GB in this version).
- 6000mAh Lithium Battery Pack: Powers the robot.
- Ackerman Steering Structure: Provides precise steering control.
- 520 Encoder Motor: Drives the wheels and provides feedback for precise movement.
5. Assembly Instructions
Detailed assembly steps are typically provided in a separate guide or video. Ensure all connections are secure and components are correctly oriented.
- Chassis Assembly: Assemble the Ackerman steering chassis, motors, and wheels.
- Mounting Main Control Board: Secure the Jetson Orin Nano Super 8GB development board onto the designated area.
- Connecting Expansion Board: Attach the ROS robot expansion board and connect it to the main control board.
- Sensor Installation: Install the depth camera, lidar, and AI voice interaction module according to the provided diagrams.
- Battery Installation: Securely place the 6000mAh lithium battery pack and connect it to the power system.
- Wiring: Connect all necessary cables for power, data, and communication between components.
Image: A close-up of the ROS robot expansion board, showing its various interfaces and components.
6. Software Setup and Configuration
The robot operates on the ROS2 system. Initial setup involves flashing the operating system and configuring network settings.
- OS Installation: Install the appropriate ROS2 distribution (e.g., ROS2 Humble) onto your Jetson Orin Nano Super 8GB board. Refer to the official Yahboom documentation for specific image files and flashing procedures.
- Network Configuration: Connect the robot to your local Wi-Fi network or establish a direct connection. This is essential for remote control and data transfer.
- Software Dependencies: Install all required software packages and libraries for the robot's functionalities (e.g., lidar drivers, camera drivers, AI vision libraries).
- Calibration: Perform initial calibration for the lidar, depth camera, and motor encoders to ensure accurate data acquisition and movement.
Image: Diagram comparing ROS1 and ROS2 system architectures, highlighting the distributed nature of ROS2.
7. Operating the Robot
The ROSMASTER R2 offers various control methods and advanced AI functions.
7.1 Remote Control
- Mobile APP Control: Download the dedicated mobile application (iOS/Android) to control the robot's movement and access real-time sensor data.
- Game Handle Control: Connect a compatible game handle (e.g., PS2 handle) for intuitive manual control.
- Keyboard Control: Use a computer keyboard to send commands to the robot via the ROS system.
Video: Demonstration of the Rosmaster R2 robot car's features, including remote control, mapping, and AI vision capabilities.
Image: Various control methods for the robot, including mobile app, FPV handle, keyboard, and Jupyter Lab control.
7.2 AI Vision and SLAM Navigation
- Lidar Mapping: Use the lidar to create 2D maps of the environment. The robot can perform gmapping, hector, karto, and cartographer mapping algorithms.
- 3D Real Scene Mapping: Utilize the depth camera for 3D environmental reconstruction and mapping.
- Navigation and Obstacle Avoidance: Program the robot to navigate autonomously through mapped environments, avoiding obstacles using sensor data.
- KCF Automatic Tracking: Implement Kernelized Correlation Filter (KCF) for real-time object tracking.
- Color Recognition and Tracking: The robot can identify and track objects based on their color.
- Autopilot: Program the robot to follow lines or predefined paths autonomously.
Image: Visual representation of lidar functions such as gmapping, hector mapping, path planning, and obstacle avoidance.
Image: Examples of AI visual recognition functions, including MediaPipe development, KCF target tracking, color identification, autopilot, AR tag recognition, and deep learning frameworks.
7.3 Voice Control
- Interactive Commands: Use predefined voice commands to control the robot's movement, navigation, and other functions.
- Voice-Controlled Navigation: Direct the robot to specific points or perform actions using voice commands.
Image: Demonstrations of multi-robot navigation, synchronized remote control, and voice interaction for controlling robot actions and lighting effects.
8. Maintenance
- Battery Care: Charge the 12V battery regularly. Avoid over-discharging or over-charging to prolong battery life.
- Cleaning: Keep sensors (lidar, camera) and wheels clean from dust and debris to ensure optimal performance.
- Software Updates: Regularly check for and install software updates for the ROS2 system and robot firmware to access new features and improvements.
- Hardware Inspection: Periodically inspect all physical connections and components for wear or damage. Tighten any loose screws.
9. Troubleshooting
| Problem | Possible Cause | Solution |
|---|---|---|
| Robot not powering on | Low battery; loose power connection | Charge battery; check power cables |
| No response to remote control | Network issue; incorrect APP settings; controller not paired | Verify Wi-Fi connection; check APP configuration; re-pair controller |
| Mapping errors or poor navigation | Dirty lidar/camera; incorrect calibration; environmental interference | Clean sensors; recalibrate; ensure clear environment |
| Voice control not working | Microphone issue; incorrect voice module setup; noisy environment | Check module connections; review setup guide; reduce background noise |
10. Specifications
| Feature | Detail |
|---|---|
| Model | ROSMASTER R2 (ULT Ver with Orin Nano Super 8GB) |
| Dimensions | 50 x 30 x 23 inches |
| Main Control Board | Jetson Orin Nano Super 8GB |
| Operating System | ROS2 (Ubuntu 22.04 LTS + ROS2 Humble) |
| Battery | 12V 6000mAh Lithium Battery |
| Steering Gear | Digital steering gear |
| Input | Astra Pro Plus depth camera, SLAM A1M8 lidar (optional), YDLIDAR 4ROS lidar (optional), AI voice interaction module (optional), PS2 wireless handle, nine-axis attitude sensor, motor speed code wheel |
| Output | RGB colorful tail lights, buzzer, 520 motor interface *4, PWM servo interface *4, OLED display |
| Connectivity | Wi-Fi network (LAN/AP) |
| Material | Anodized aluminum alloy |
Image: Detailed product parameters table and dimensional diagrams for the ROSMASTER R2 robot.
11. Support and Resources
For further assistance, tutorials, and community support, please refer to the official Yahboom resources:
- Official Website: Visit the Yahboom official website for product information and updates.
- Online Documentation: Access detailed tutorials and guides for ROS1 and ROS2 development.
- Community Forums: Engage with other users and developers for troubleshooting and project ideas.
Image: An overview of the extensive course content and tutorials available for the ROSMASTER R2, covering ROS1, ROS2, Docker, and various AI applications.
