Waveshare UGV Beast ROS 2 – Pan-Tilt

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.

Powered by the high-performance Raspberry Pi or Jetson Orin series computer (none included) 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!

Dual-controller design, provides efficient collaboration and upgraded performance

The host controller adopts Jetson Orin Nano or Raspberry Pi for AI vision and strategy planning, and the sub controller uses ESP32 for motion control and sensor data processing. Improves the processing efficiency and response speed of the host computer without bearing all tasks. The sub controller focuses on basic functions to ensure the accurate and smooth actions of robot.

Ubuntu 22.04 / Raspberry Pi OS & ROS2 Docker

Ensures advanced decision-making performance of robot and system compatibility at the same time. Supports all AI functions of the previous AI Kit series products.

360° flexible omnidirectional Pan-Tilt

Equipped with 5MP 160° wide-angle camera for capturing every detail.

Open source for all ROS 2 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 ROS 2 mapping methods

Meet the needs of mapping in different scenarios.

Recognition, tracking, and targeting

Based on OpenCV to achieve Color Recognition and automatic targeting. Supports one-key Pan-Tilt control and automatic LED lighting, allows expansion for more functions.

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.

Intelligent Object Recognition

Supports recognizing for many common objects with the default model.

Gesture Recognition: AI interaction with body language

Combines OpenCV and MediaPipe to realize gesture control of Pan-Tilt and LED.

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 the mapping, suitable for unmanned 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.

ROS2 node command interaction

Users can send control commands to the robot by a script for performing operations such as moving, obtaining the current location, and navigating to a specific point, etc. which is more convenient for secondary development.

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.

Technical data

Standard aluminum rail

Comes with 2×1020 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.

Easy to control via cross-platform web application

No App installation required, allows users to connect and control the robot via mobile phones, tablets and computers via browser Web App. Supports shortcut key control such as WASD and the mouse via a PC with keyboard.

Real-time wireless transmission of high frame rate video

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.

More MediaPipe demos for easily creating complex video processing tasks

MediaPipe is an open-source framework developed by Google for building cross-platform multimedia processing pipelines, provides a set of pre-built components and tools, its high-performance processing capability enables the robot to respond to and process complex multimedia inputs such as real-time video analytics.

Obtains real-time information feedback

Real-time monitoring the operating status of the robot.

Web page command line tool, multiple functions for easier expansion

Quick to set up, easy to expand. Easily customize and add new functions without modifying front-end code.

ESP-NOW wireless communication between robots

Based on ESP-NOW communication protocol, multiple robots can communicate with each other without IP or MAC address, achieving multi-device collaboration with 100-microsecond low-latency communication.

Gamepad control for better operation experience

Comes with a wireless gamepad, making robot control more flexible. You can connect the USB receiver to your PC and control the robot remotely via the internet. Provides open source demo for customizing your own interaction method.

Realizes remote control across the internet

Our web application demos are based on WebRTC for real-time video transmission. WebRTC (Web Real-Time Communications) is a technology that enables web applications and sites to establish peer-to-peer connection and capture optionally stream audio and/or video media, as well as to exchange arbitrary data between browsers without requiring an intermediary. We provide comprehensive Ngrok tutorials to help you get started quickly and realize robot control across the internet.

Supports installing smartphone holder

If you have a spare phone, you can install it on the robot via holder as below, using the phone to create a hotspot for the robot and achieving remote control across the internet at a lower cost. It comes with a smartphone holder with 1/4″ screw in the package.

Cross-platform interactive tutorial, develop while you learn

Supports accessing Jupyter Lab via devices such as mobile phones and tablets to read the tutorials and edit the code on the web page, making development easier.

Rich tutorial resources

We provide complete tutorials and demos to help users get started quickly for learning and secondary development.