WAVE-28861 UGV Beast ROS 2 Open-source Off-Road Tracked AI Robot, Dual controllers, Computer Vision, All-metal Body, Suitable for Raspberry Pi 5 (Pan-Tilt Included). Raspberry 5 not included.
Features At A Glance
The UGV Beast ROS2 Kit is an AI robot designed for exploration and creation with excellent expansion potential, based on ROS 2 and equipped with Lidar and depth camera, seamlessly connecting your imagination with reality. Suitable for tech enthusiasts, makers, or beginners in programming, it is your ideal choice for exploring the world of intelligent technology.
Equipped with the high-performance Raspberry Pi computer to meet the challenges of complex strategies and functions, and inspire your creativity. Adopts dual-controller design, combines the high-level AI functions of the host controller with the high-frequency basic operations of the sub controller, making every operation accurate and smooth.
Easy to be controlled remotely via UGV Beast Web Application without downloading any software, just open your browser and start your journey. You can use the basic ROS 2 functions of the robot without installing a virtual machine on the PC. Supports high-frame rate real-time video transmission and multiple AI Computer Vision functions, the UGV Beast is an ideal platform to realize your ideas and creativity.
Specifications
Dimensions: 196.82x231.46x251.78mm
Weight: ~2411g
Chassis Height: 25mm
Pan-Tilt DOF: 2
Pan-Tilt Servo Torque: 30kg.cm
Pan-Tilt Servo: ST3215 Servo
Host Controller: Raspberry Pi 5 / 4B (NOT included)
Host System Support: Debian Bookworm
ROS2 Version: ROS2-HUMBLE-LTS
Camera FOV: 160°
Power Supply: 3S UPS Module
Battery Support: 3x 18650 Lithium Battery (NOT included)
Demo Control Methods: Web application / Jupyter Lab interactive programming
Default Max Speed: 0.35m/s
Number of Driving Wheels: 2
Suspension Material: Stainless Steel
Tire Width: 40mm
Minimum Turning Radius: 0M (In-situ rotation)
Based On Raspberry Pi
Supports Raspberry Pi 5 / 4B, With Powerful Computing Performance To Handle More Complex Tasks, Offering More Possibilities
Collaboration and Upgraded Performance
The Host Controller Adopts Raspberry Pi For AI Vision and Strategy Planning, and the Sub Controller Uses ESP32 For Motion Control and Sensor Data Processing
Raspberry Pi OS + ROS2 Docker
Ensures Advanced Decision-Making Performance of Robot and System Compatibility At the Same Time
360° Flexible Omnidirectional Pan-Tilt
Equipped with 5MP 160° Wide-Angle Camera For Capturing Every Detail
Open Source for All ROS2 Development Resources
Open Source For All Demos of Host Controller and Sub Controller, Including Robot Description File (URDF Model), Sensor Data Processing Node of Sub Controller, Kinematic Control Algorithms, and Various Remote Control Nodes
Integrates Various ROS2 Mapping Methods
Meet the Needs of Mapping in Different Scenarios
Multiple Cost-Effective Sensors
Adopts Multiple Sensors with High Cost-Effectiveness and Practicality
Auto Exploration and Mapping
Using SLAM Toolbox To Implement Mapping and Navigation Functions Simultaneously in Unknown Environments, Simplifying the Task Execution Process. The UGV Robot Can Autonomously Explore Unknown Areas and Complete he Mapping, Suitable for Unmannered Applications
Supports Natural Language Interaction
Adopts Large Language Model (LLM) Technology, Users Can Give Commands To The Robot By Natural Language, Enabling It To Perform Tasks Such As Moving, Mapping, and Navigation
Provides Web Console Tool
You Can Use The Basic ROS 2 Functions on the Web Without Installing a Virtual Machine on the PC, Supports Cross-Platform Operation On Android Or IOS Tablets. Users Can Simply Open a Browser and Control the Robot for Moving, Mapping, Navigation and other Operations
Gazebo Simulation Debugging
Provides Gazebo Robot Mode and Complete Functionality Library for Simulation Debugging, Helping You Verify and Test the System During the Early Stages of Development
Continuing the Adventure as Night Falls
High-Brightness LED Light for Ensuring Clear Images in Low-Light Conditions
Suitable for Tactical Extension
Comes with 21mm Wide Rail and 30kg.cm High Precision & High-Torque Bus Servo for Tactical Extension
Standard Aluminum Rail
Comes with 2x1020 European Standard Profile Rails, and Supports Installing Additional Peripherals via the Boat Nuts to Meet Different Needs, Easily Expanding the Special Operation Scenarios
Supports Driving in Complex Terrain
Adopts Tracked Mobile Robot Chassis With Independent Suspension Systems For More Stable Off-Road Crossing Ability
WebRTC Real-Time Video Transmission
Adopts Flask Lightweight Web Application, Based on WebRTC Ultra-low Latency Real-Time Transmission, Using Python Language and Easy to Extend, Working Seamlessly with OpenCV
Face Detection: Automatic Picture or Video Capturing
Based on OpenCV to Achieve Face Recognition, Supports Automatic Photo Taking or Video Recording Once a Face is Recognized
Gesture Recognition: AI Interaction with Body Language
Combines OpenCV and MediaPipe to Realize Gesture Control of Pan-Tilt and LED
40Pin GPIO Extended Header
The Robot Only Occupies the URAT Interface of the Raspberry Pi GPIO For Communication, Adapting Outer Side 40Pin Header of the Driver Board for Expanding More Peripherals and Functions
ESP-NOW Wireless Communication Between Robots
Based on ESP-NOW Communication Protocol, Multiple Robots can Communicate with Each Other Without IP or MAC Addresses, Achieving Multi-Device Collaboration with 100-microsecond Low-Latency Communication
Outline Dimensions
Package Content
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