Yahboom ROS2 Robot Engineering Programming Development, Hex-Leg Robot Raspberry Pi AI Large Model Voice Module, Supports 4ROS LiDAR, Servo, SLAM
MNT 5911663
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Equipped with Raspberry Pi & ROS2, the MUTO RS is designed for innovative biomimic AI projects and robust physical AI applications.
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What Stands Out
Бүтээгдэхүүний дэлгэрэнгүй мэдээлэл
- Equipped with Raspberry Pi & ROS2: The MUTO RS is a Raspberry Pi 5 based hexagon robot, and supports the Robot Operating System ROS2. Integrates Python, AI deep learning framework, reverse kinesiology algorithms, ideal for developing biomimic AI and polypod projects
- Equipped with a large AI model, advanced human-to-computer interaction: The openRouter builds an interactive system based on three AI models. It incorporates 3D vision, identify scenes written by commands, then use multi-modal vision to determine whether the scene on the screen matches the description, enabling navigation and AI visual game play. Superior environmental perception, reasoning, and intellectual execution ability to achieve more advanced physical AI applications
- High Performance Hardware Configuration Upgraded AI large model voice module supports AI large model deployment data and access to multi-modal applications. Astra Pro Plus depth camera not only completes high-definition AI visual capabilities, but also handles deep image data processing and 3D navigation mapping. YDLIDAR 4ROS/A1 LiDAR meets precision requirements for large indoor and outdoor scenes
- Hexagon Motion Research, Multi-Platform Control: The hexagon robot has 3 kinetic joint points on each leg, achieves a total of 18 degrees of freedom, bio-mimic hexagonal joint movement, 270° controllable, 77.5 lbs 35 kg intelligent serial bus servo, and freely adjustable height. Enjoy remote control using apps, radio controllers and host computers. The combination of the controller and app allows you to realize the robots first person view remote control and experience FPV real-time video transmission
- Advanced AI Technology and Comprehensive Tutorials MUTO RS guides a series of cutting-edge technologies, including ROS2 development, deep vision, AI large model, OpenCV, robotic reverse kinesiology, MoveI, Rviz simulation, and AI voice interaction. We offer deep learning materials and video tutorials
| Brand Name | Yahboom |
| Manufacturer | Yahboom |
| Country of Publication | China |
| Manufacturer Part Number | MUTO-RS 4ROS |
| Size | 4ROS Ver with Pi5-16GB |
| Item Weight | 4.5 lbs (2.04 kg) |
Who Should Buy?
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Robotics Enthusiasts
Ideal for hobbyists who enjoy building and programming advanced robotic systems with AI capabilities.
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Educational Institutions
Great for schools and universities offering courses in robotics, AI, and programming, providing hands-on experience.
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Research Developers
Perfect for researchers needing a customizable platform for experimenting with SLAM and navigation technologies.
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Casual Users
Not suitable for those looking for simple, ready-to-use robotics solutions without any programming or development requirements.
БАРААНЫ ТАЙЛБАР
Хэрэглэгчийн асуулт, хариулт
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Асуулт:
What is the main feature of the MUTO RS?
Хариулт: The MUTO RS supports Raspberry Pi 5 and ROS2, enabling advanced AI and biomimicry projects. -
Асуулт:
Can the MUTO RS be used for educational purposes?
Хариулт: Yes, the MUTO RS is perfect for educational projects focused on robotics and AI development. -
Асуулт:
Does the MUTO RS support deep learning frameworks?
Хариулт: Yes, it utilizes popular deep learning frameworks for enhanced AI processing capabilities.
Yahboom Editorial Review
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Product Price History
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MNT 5911663
Яг одоо захиалаад ойрын хугацаанд хүлээн аваарай Пүрэв гараг, 8 дугаар сар 27
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Онцлог & Давуу талууд
- Supports Raspberry Pi 5 and ROS2 for seamless integration.
- Utilizes deep learning frameworks for powerful AI capabilities.
- Features advanced 3D vision and human-to-computer interaction.
- Ideal for developing biomimic AI and polypod projects.
- Offers superior environmental perception and reasoning.
- Perfect for advanced physical AI applications.
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