Commercial model
$264.99 list price
A published price gives buyers a starting point for budgeting, ROI modeling, and peer comparison before deeper vendor conversations begin.
Robot dossier
UGV Beast
Release
Apr 21, 2026
Price
$265
Connectivity
6
Status
Available
Height
122 mm without pan-tilt; 252 mm with PT camera
Weight
2.034 kg without pan-tilt; 2.35 kg with PT camera
Speed
0.35 m/s default max speed
Research
Available
UGV Beast
Waveshare's UGV Beast is an open-source off-road tracked AI robot platform for Raspberry Pi 4B or Raspberry Pi 5 developers. The official store page and wiki describe a dual-controller architecture: the Raspberry Pi handles higher-level AI vision, WebRTC browser control, JupyterLab tutorials, and strategy code while an ESP32 sub-controller handles motor PID, IMU data, pan-tilt/LED control, OLED status, battery sensing, and ESP-NOW communication. The tracked aluminum chassis adds independent suspension, zero-radius turning, optional 2-DOF pan-tilt with a 5MP 160-degree camera, OpenCV/MediaPipe demos for face, object, color, gesture, and line tracking, and hardware expansion for LiDAR, 4G/5G, audio, and GPIO peripherals. It is a maker and research platform rather than a consumer home-helper robot, but it clears ui44's bar through its open software stack, dual-controller design, computer-vision demos, and rugged mobile-robot hardware.
Listed price
$265
Official Waveshare store page lists UGV Beast kit variants from US$264.99 to US$500.99 depending on Raspberry Pi 4B/5, pan-tilt, and accessory configuration; 18650 batteries are not included.
Release window
Apr 21, 2026
Current status
Available
Waveshare
Last verified
May 27, 2026
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Technical overview
Core specifications and system stack
A fast read on the mechanical profile, sensing package, and platform integrations behind UGV Beast.
Technical Specifications
Height
122 mm without pan-tilt; 252 mm with PT camera
Weight
2.034 kg without pan-tilt; 2.35 kg with PT camera
Dimensions
232 x 197 x 122 mm base; 232 x 197 x 252 mm with PT camera
Battery Life
Not officially disclosed; uses 3x 18650 lithium cells with a 3S UPS module, batteries not included
Charging Time
Not officially disclosed; UPS module supports charging and discharging at the same time
Max Speed
0.35 m/s default max speed
Tech Components
Sensors (6)
Operational profile
How this robot is configured
Capabilities
14
Connectivity
6
Key capabilities
Open-source mobile robotics platformOff-road tracked chassis with independent suspensionDual-controller Raspberry Pi + ESP32 architectureBrowser-based WebRTC remote control and video streamingOpenCV color recognition and automatic targetingFace detection and media captureObject recognition demosGesture recognition with MediaPipe
Ecosystem fit
Raspberry Pi 4BRaspberry Pi 5Debian BookwormROS2 HumblePythonFlask
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About the UGV Beast
6Sensors6Protocols14Capabilities$0.3kListed Price
The UGV Beast is a Research robot built by Waveshare. Waveshare's UGV Beast is an open-source off-road tracked AI robot platform for Raspberry Pi 4B or Raspberry Pi 5 developers. The official store page and wiki describe a dual-controller architecture: the Raspberry Pi handles higher-level AI vision, WebRTC browser control, JupyterLab tutorials, and strategy code while an ESP32 sub-controller handles motor PID, IMU data, pan-tilt/LED control, OLED status, battery sensing, and ESP-NOW communication. The tracked aluminum chassis adds independent suspension, zero-radius turning, optional 2-DOF pan-tilt with a 5MP 160-degree camera, OpenCV/MediaPipe demos for face, object, color, gesture, and line tracking, and hardware expansion for LiDAR, 4G/5G, audio, and GPIO peripherals. It is a maker and research platform rather than a consumer home-helper robot, but it clears ui44's bar through its open software stack, dual-controller design, computer-vision demos, and rugged mobile-robot hardware.
At a listed price of $264.99, it positions itself in the consumer-accessible segment of the research market. See all Waveshare robots on the Waveshare page.
Spec Breakdown
Detailed specifications for the UGV Beast
Height
122 mm without pan-tilt; 252 mm with PT cameraAt 122 mm without pan-tilt; 252 mm with PT camera, the UGV Beast is sized for its intended operating environment and use cases.
Weight
2.034 kg without pan-tilt; 2.35 kg with PT cameraWeighing 2.034 kg without pan-tilt; 2.35 kg with PT camera, the UGV Beast balances structural integrity with portability and maneuverability.
Dimensions
232 x 197 x 122 mm base; 232 x 197 x 252 mm with PT cameraThe overall dimensions of 232 x 197 x 122 mm base; 232 x 197 x 252 mm with PT camera define the robot's physical footprint and determine what spaces it can navigate and what clearances it requires for operation.
Maximum Speed
0.35 m/s default max speedA top speed of 0.35 m/s default max speed is calibrated for the robot's primary operating environment and safety requirements.
The UGV Beast uses Raspberry Pi 4B/5 host running Debian Bookworm with open-source Flask/WebRTC and JupyterLab tutorials; OpenCV and MediaPipe demos cover color recognition, automatic targeting, face detection, object recognition, gesture control, and vision line tracking, while the ESP32 sub-controller handles real-time motion/sensor loops. as its intelligence backbone. This AI platform powers the robot's decision-making, perception processing, and autonomous behavior. The sophistication of the AI stack directly impacts how well the robot handles unexpected situations and adapts to new environments.
UGV Beast Sensor Suite
The UGV Beast integrates 6 sensor types, forming the perceptual foundation that enables autonomous operation.
Optional 5MP 160-degree camera on 2-DOF pan-tilt
Details →
ICM20948 9-axis IMU
Details →
Motor encoders for closed-loop speed control
Details →
INA219 battery-voltage monitoring
Details →
Dual-track microphone and speaker audio board
Details →
Expansion space/interfaces for D500 or STL-27L LiDAR
Details →
This sensor configuration enables the UGV Beast to perceive its environment and operate autonomously in its intended use cases. Multiple sensor modalities provide redundancy and more robust perception than any single sensor type alone.
Explore sensor technologies: components glossary · full components directory
UGV Beast Use Cases & Applications
Research robots serve as platforms for advancing robotics science and engineering. They enable researchers to test theories about locomotion, manipulation, perception, and human-robot interaction in controlled and real-world environments.
Capabilities That Enable Real-World Use
The UGV Beast offers 14 distinct capabilities, each contributing to the robot's practical utility.
Open-source mobile robotics platform
Off-road tracked chassis with independent suspension
Dual-controller Raspberry Pi + ESP32 architecture
Browser-based WebRTC remote control and video streaming
OpenCV color recognition and automatic targeting
Face detection and media capture
Object recognition demos
Gesture recognition with MediaPipe
Vision line tracking for autonomous-driving tutorials
2-DOF camera pan-tilt control and vertical stabilization
ESP-NOW multi-robot communication
JupyterLab and Python development workflow
ROS2 Humble tutorial support
LiDAR, GPIO, audio, and cellular expansion
These capabilities work together with the robot's 6 onboard sensor types and Raspberry Pi 4B/5 host running Debian Bookworm with open-source Flask/WebRTC and JupyterLab tutorials; OpenCV and MediaPipe demos cover color recognition, automatic targeting, face detection, object recognition, gesture control, and vision line tracking, while the ESP32 sub-controller handles real-time motion/sensor loops. AI platform to deliver practical, real-world performance.
Ecosystem Integration
The UGV Beast integrates with the following platforms and ecosystems, extending its utility beyond standalone operation.
Raspberry Pi 4B
Raspberry Pi 5
Debian Bookworm
ROS2 Humble
Python
Flask
WebRTC
OpenCV
MediaPipe
JupyterLab
ESP-NOW
This ecosystem compatibility enables the UGV Beast to work as part of a broader automation setup rather than operating in isolation.
UGV Beast Capabilities
14
Capabilities
6
Sensor Types
AI
Raspberry Pi 4B/5 host runni…
Open-source mobile robotics platform
Off-road tracked chassis with independent suspension
Dual-controller Raspberry Pi + ESP32 architecture
Browser-based WebRTC remote control and video streaming
OpenCV color recognition and automatic targeting
Face detection and media capture
Object recognition demos
Gesture recognition with MediaPipe
Vision line tracking for autonomous-driving tutorials
2-DOF camera pan-tilt control and vertical stabilization
ESP-NOW multi-robot communication
JupyterLab and Python development workflow
ROS2 Humble tutorial support
LiDAR, GPIO, audio, and cellular expansion
Connectivity & Integration
How the UGV Beast communicates with your network, smart home devices, cloud services, and companion apps.
Network & Communication Protocols
Wi-Fi and Ethernet via Raspberry Pi host
Details →
Bluetooth via Raspberry Pi host
Details →
ESP32 Wi-Fi / Bluetooth / ESP-NOW
Details →
Browser Web App with WebRTC video
Details →
USB gamepad receiver support
Details →
Optional 4G/5G module expansion
Details →
✓ Wi-Fi for local network and cloud access · ✓ Bluetooth for direct device pairing — enabling the UGV Beast to participate in various networking scenarios.
UGV Beast Technology Stack Overview
The UGV Beast by Waveshare integrates 13 distinct technology components across sensing, connectivity, intelligence, and interaction layers. The physical platform features a height of 122 mm without pan-tilt; 252 mm with PT camera, a weight of 2.034 kg without pan-tilt; 2.35 kg with PT camera, a top speed of 0.35 m/s default max speed, providing the foundation on which this technology stack operates.
Perception — 6 Sensor Types
The perception layer is built on Optional 5MP 160-degree camera on 2-DOF pan-tilt, ICM20948 9-axis IMU, Motor encoders for closed-loop speed control, INA219 battery-voltage monitoring, Dual-track microphone and speaker audio board, Expansion space/interfaces for D500 or STL-27L LiDAR. These work in concert to give the robot a detailed understanding of its operating environment. This multi-sensor approach provides redundancy and enables the robot to function reliably even when individual sensors encounter challenging conditions such as low light, reflective surfaces, or cluttered spaces.
Connectivity — 6 Protocols
For communications, the UGV Beast relies on Wi-Fi and Ethernet via Raspberry Pi host, Bluetooth via Raspberry Pi host, ESP32 Wi-Fi / Bluetooth / ESP-NOW, Browser Web App with WebRTC video, USB gamepad receiver support, Optional 4G/5G module expansion. This connectivity stack ensures the robot can communicate with cloud services, local smart home devices, mobile apps, and other networked systems in its environment.
Intelligence — Raspberry Pi 4B/5 host running Debian Bookworm with open-source Flask/WebRTC and JupyterLab tutorials; OpenCV and MediaPipe demos cover color recognition, automatic targeting, face detection, object recognition, gesture control, and vision line tracking, while the ESP32 sub-controller handles real-time motion/sensor loops.
Raspberry Pi 4B/5 host running Debian Bookworm with open-source Flask/WebRTC and JupyterLab tutorials; OpenCV and MediaPipe demos cover color recognition, automatic targeting, face detection, object recognition, gesture control, and vision line tracking, while the ESP32 sub-controller handles real-time motion/sensor loops. serves as the computational brain, processing sensor data, making navigation decisions, and orchestrating the robot's autonomous behaviors. The quality of this AI platform directly influences how well the robot handles novel situations, adapts to changes in its environment, and improves its performance over time through learning.
Who Should Consider the UGV Beast?
Target Audience
Research robots are acquired by universities, government labs, and corporate R&D departments. They serve as experimental platforms for developing new algorithms, testing locomotion strategies, and advancing the field of robotics. Some are also used for educational purposes.
Key Considerations
Open-source software compatibility (ROS/ROS 2), sensor modularity, programmability, available SDK/API quality, community support, and published research papers using the platform are key factors. Documentation quality and the ability to modify both hardware and software are essential for research use.
Price Context
At $264.99 (Official Waveshare store page lists UGV Beast kit variants from US$264.99 to US$500.99 depending on Raspberry Pi 4B/5, pan-tilt, and accessory configuration; 18650 batteries are not included.), the UGV Beast sits in the budget price tier for research robots. This competitive price point makes the technology accessible to a broad consumer base.
Availability
AvailableThe UGV Beast is currently available for purchase. Check the manufacturer's website or authorized retailers for the latest stock and ordering information.
UGV Beast: Strengths & Trade-offs
Engineering compromises and where this research robot excels
What the UGV Beast does well
Extensive sensor suite
With 6 sensor types onboard, the UGV Beast has one of the more comprehensive perception systems in the research category. This multi-modal approach enables robust environmental awareness, redundant obstacle detection, and reliable autonomous operation even in challenging conditions. More sensor diversity generally translates to better real-world adaptability.
Versatile connectivity
Supporting 6 connectivity protocols gives the UGV Beast flexible integration options. Whether connecting to local smart home networks, cloud services, or companion devices, the breadth of connectivity ensures compatibility across a wide range of deployment scenarios and reduces the risk of network-related limitations.
Broad capability set
With 14 distinct capabilities, the UGV Beast is designed as a versatile platform rather than a single-task device. This breadth means the robot can handle varied scenarios and workflows, reducing the need for multiple specialized robots and increasing its utility across different situations.
Currently available
Unlike many robots that remain in development or prototype stages, the UGV Beast is available for purchase today. This means you can evaluate the actual shipping product rather than making decisions based on projected specifications that may change before release.
Accessible price point
At $264.99, the UGV Beast is competitively priced within the research market. This price point makes the technology accessible to a broader audience and represents a lower barrier to entry for those exploring research robotics.
Note: This strengths and trade-offs assessment is based on the UGV Beast's documented specifications as tracked in the ui44 database. Real-world performance depends on deployment conditions, firmware maturity, and environmental factors. For the most current information, check the Waveshare manufacturer page or visit the official product page. Use the comparison tool to evaluate these trade-offs against competing robots in the same category.
How Research Robot Technology Works
Understanding the engineering behind this category
Research robots serve a fundamentally different purpose than commercial or consumer models. They are platforms for discovery — enabling scientists and engineers to test theories, develop algorithms, and push the boundaries of what robots can do. The technology in research robots prioritizes openness, flexibility, and access to raw data over consumer-friendly packaging or commercial reliability. Understanding this distinction is important for anyone considering a research robot platform.
Navigation & Mobility
Research robots typically expose their navigation systems at a much lower level than commercial products. Researchers can access raw sensor data, modify SLAM algorithms, implement custom path planners, and test novel navigation approaches. ROS (Robot Operating System) and ROS 2 compatibility is standard, providing a common framework for sharing navigation modules across the research community. This openness enables rapid iteration — a researcher can swap between different SLAM implementations, test new obstacle avoidance strategies, or develop entirely novel navigation paradigms without being locked into a vendor's proprietary stack.
The Role of AI
Research robots serve as physical testbeds for AI algorithms that may eventually appear in commercial products years later. Reinforcement learning, imitation learning, few-shot task learning, and human-robot interaction studies all require robot platforms that can execute AI-generated commands in the physical world. The gap between simulation (where training is cheap and fast) and reality (where physics is unforgiving) makes physical robot platforms essential for validating AI approaches. Research robots must support rapid deployment of new AI models without extensive integration work.
Sensor Fusion & Perception
Research platforms prioritize sensor modularity and data access. Standard mounting interfaces allow researchers to attach custom sensors alongside built-in ones. Raw sensor data streams (not just processed results) are accessible for developing novel perception algorithms. Precise time-stamping and synchronization across sensor streams enable accurate multi-modal fusion research. Many research robots include more sensors than strictly necessary for any single application, providing researchers with rich datasets for developing and testing new algorithms.
Power & Battery Management
Research robots balance operational runtime with practical lab use. Sessions of one to four hours are typical, with quick charging between experiments. Some research setups use tethered power for long-running experiments where battery limitations would interrupt data collection. Power monitoring and logging capabilities help researchers understand the energy costs of different behaviors and algorithms — important for developing efficient approaches that will eventually run on battery-constrained commercial systems.
Safety by Design
Research environments present unique safety challenges because robots are constantly being programmed with untested behaviors. Hardware safety limits (joint speed caps, force limits, emergency stops) must be robust regardless of software commands. Safety-rated monitored stop and speed monitoring ensure the robot cannot exceed safe operating parameters even when running experimental code. Collaborative operation standards apply when researchers work alongside the robot during experiments. Many labs implement layered safety with physical barriers for high-speed testing and open-area operation restricted to validated, lower-risk behaviors.
What's Next for Research Robots
Research robot platforms are becoming more accessible and capable. Cloud robotics enables remote experiment execution and shared datasets. Digital twins and high-fidelity simulators reduce the need for physical hardware time while improving sim-to-real transfer. Standardized benchmarks and open datasets enable fair comparison of results across labs. The democratization of robotics research — through lower-cost platforms, open-source software, and cloud infrastructure — is expanding who can contribute to advancing the field.
The UGV Beast by Waveshare incorporates many of these technology pillars. For a detailed look at the specific sensors and components used in the UGV Beast, see the sensor analysis and connectivity sections above, or browse the complete components glossary for explanations of every technology used across the robotics industry.
UGV Beast in the Research Market
How this robot compares in the research landscape
At $264.99, the UGV Beast competes in the entry-level segment of the research market, where affordability is the primary consideration for most buyers.
With 6 sensor types, the UGV Beast has an extensive sensor suite. This comprehensive sensing capability places it among the more perception-capable robots in the research category, enabling more robust autonomous operation in varied conditions.
Being currently available for purchase gives the UGV Beast a practical advantage over competitors still in development or prototype stages. Buyers can evaluate the actual product rather than relying on spec-sheet promises that may change before release.
Head-to-Head Comparisons
Side-by-side specs, capability overlap analysis, and key differentiators.
For the full picture of Waveshare's portfolio and market strategy, visit the Waveshare manufacturer page.
Deployment Readiness and Procurement Signals for UGV Beast
What the public profile tells you, and what still needs direct vendor confirmation
From a buying and rollout perspective, the UGV Beast should be read as a research platform aimed at labs and development teams validating robotics workflows. ui44 currently tracks 14 capability signals, 6 sensor inputs, and a last verification date of 2026-05-27. That mix gives buyers a useful first-pass picture, but it is still only the public layer of due diligence, especially when procurement, uptime, and support commitments are decided directly with Waveshare.
Integration posture
6 connectivity options
The profile lists Wi-Fi and Ethernet via Raspberry Pi host, Bluetooth via Raspberry Pi host, ESP32 Wi-Fi / Bluetooth / ESP-NOW, Browser Web App with WebRTC video, USB gamepad receiver support, Optional 4G/5G module expansion, plus Raspberry Pi 4B/5 host running Debian Bookworm with open-source Flask/WebRTC and JupyterLab tutorials; OpenCV and MediaPipe demos cover color recognition, automatic targeting, face detection, object recognition, gesture control, and vision line tracking, while the ESP32 sub-controller handles real-time motion/sensor loops. as the AI stack. That is enough to infer the basic network posture, but buyers should still confirm APIs, fleet management, and workflow integration details. ui44 currently tracks 11 declared compatibility links.
Spec disclosure
4/7 core specs public
ui44 currently has 4 of 7 core physical and operating specs filled in for this model, leaving 3 gaps that matter for deployment planning. Missing runtime, charge, speed, or payload details can materially change staffing and site-readiness assumptions.
The current profile is useful for scouting, but it still leaves meaningful operational unknowns. If this robot is heading toward a pilot or purchase discussion, the next step should be a structured vendor Q&A that fills the remaining runtime, charging, payload, safety, or integration blanks before anyone builds ROI assumptions around it.
If you want a faster apples-to-apples read, compare the UGV Beast against nearby alternatives in ui44's compare view, then cross-check the underlying AI, sensor, and subsystem terms in the components glossary. For manufacturer-level context, the Waveshare profile helps anchor this robot inside the wider product lineup.
Before you sign off on a pilot, confirm these points
- Ask for real shift runtime under the intended workload, not just standby endurance.
- Confirm how the charging workflow works in practice, including charger count, swap options, and expected downtime.
- Clarify usable payload or tool-load limits before planning material handling or mounted accessories.
- Check what safety, electrical, or deployment certifications exist for the region and task you care about.
Owning the UGV Beast: Setup, Maintenance & Tips
Practical guide from day one through years of ownership
Initial Setup
Research robot setup combines hardware assembly with software environment configuration. Unpack and assemble the platform following the manufacturer's documentation. Install the development framework — typically ROS or ROS 2 — and verify sensor connectivity. Calibrate all sensors using the manufacturer's tools and procedures. Set up the simulation environment (Gazebo, Isaac Sim, or equivalent) alongside the physical platform for parallel development. Establish version control for your experiment code and configuration. Document the initial calibration values and system state as your baseline for future reference. Plan network and computing infrastructure to handle the data rates your sensors will generate.
Ongoing Maintenance
Research robots need maintenance that preserves the precision required for valid experimental results. Regularly verify sensor calibration — drift in camera intrinsics or IMU biases can invalidate experiment data. Maintain clean workspace conditions to protect optical sensors. Document any hardware modifications or maintenance performed, as these can affect experimental reproducibility. Update software dependencies carefully, documenting versions used for each experiment. Joint and actuator wear in research robots that perform repetitive tasks should be monitored and factored into experimental design.
Software Updates & Long-Term Support
Research robot software updates require careful management to maintain experiment reproducibility. Document the exact software versions used for each experiment. Test updates in a separate environment before applying to your experiment platform. Contribute bug fixes and improvements back to the community when using open-source frameworks. Be aware that ROS and other framework updates may require code changes in your custom packages — budget time for integration testing after major framework updates.
Maximizing Longevity
Research robots often have longer productive lives than commercial products because they can be upgraded and repurposed. Extend your investment by maintaining clean mechanical and electrical systems, documenting all modifications for future lab members, and keeping spare parts for common wear items. When specific components become obsolete, community forums and lab networks can be valuable sources for replacements. Consider the platform's modularity when planning future research directions — a platform that can accept new sensors and actuators adapts to evolving research questions.
For Waveshare-specific support resources and documentation, visit the Waveshare page on ui44 or check the manufacturer's official website at Waveshare's product page.
Frequently Asked Questions
What is the UGV Beast?
The UGV Beast is a Research robot made by Waveshare. Waveshare's UGV Beast is an open-source off-road tracked AI robot platform for Raspberry Pi 4B or Raspberry Pi 5 developers. The official store page and wiki describe a dual-controller architecture: the Raspberry Pi handles higher-level AI vision, WebRTC browser control, JupyterLab tutorials, and strategy code while an ESP32 sub-controller handles motor PID, IMU data, pan-tilt/LED control, OLED status, battery sensing, and ESP-NOW communication. The tracked aluminum chassis adds independent suspension, zero-radius turning, optional 2-DOF pan-tilt with a 5MP 160-degree camera, OpenCV/MediaPipe demos for face, object, color, gesture, and line tracking, and hardware expansion for LiDAR, 4G/5G, audio, and GPIO peripherals. It is a maker and research platform rather than a consumer home-helper robot, but it clears ui44's bar through its open software stack, dual-controller design, computer-vision demos, and rugged mobile-robot hardware. It features 6 sensor types, 6 connectivity protocols, and 14 distinct capabilities.
How much does the UGV Beast cost?
The UGV Beast is listed at $264.99 (Official Waveshare store page lists UGV Beast kit variants from US$264.99 to US$500.99 depending on Raspberry Pi 4B/5, pan-tilt, and accessory configuration; 18650 batteries are not included.). This places it in the budget-friendly consumer tier for research robots. Prices may vary by region and retailer.
Is the UGV Beast available to buy?
Yes, the UGV Beast is currently available for purchase. Check Waveshare's official website or authorized retailers for the latest stock and ordering options.
What sensors does the UGV Beast have?
The UGV Beast is equipped with 6 sensor types: Optional 5MP 160-degree camera on 2-DOF pan-tilt, ICM20948 9-axis IMU, Motor encoders for closed-loop speed control, INA219 battery-voltage monitoring, Dual-track microphone and speaker audio board, Expansion space/interfaces for D500 or STL-27L LiDAR. These sensors work together through sensor fusion to provide comprehensive environmental awareness for autonomous operation. See the sensor analysis section for details.
What AI does the UGV Beast use?
The UGV Beast is powered by Raspberry Pi 4B/5 host running Debian Bookworm with open-source Flask/WebRTC and JupyterLab tutorials; OpenCV and MediaPipe demos cover color recognition, automatic targeting, face detection, object recognition, gesture control, and vision line tracking, while the ESP32 sub-controller handles real-time motion/sensor loops.. This AI platform handles the robot's perception processing, decision-making, and autonomous behavior. The sophistication of the AI directly impacts how well the robot handles unexpected situations, learns from its environment, and improves over time.
How does the UGV Beast compare to the WiXus?
The UGV Beast and WiXus are both research robots, but they differ in key specifications, pricing, and manufacturer approach. Use the side-by-side comparison tool to see detailed differences in specs, sensors, and capabilities. You can also browse other similar robots below.
Does the UGV Beast work with smart home systems?
Yes, the UGV Beast is compatible with: Raspberry Pi 4B, Raspberry Pi 5, Debian Bookworm, ROS2 Humble, Python, Flask, WebRTC, OpenCV, MediaPipe, JupyterLab, ESP-NOW. This ecosystem integration allows the robot to work alongside your existing smart home devices and platforms rather than operating as an isolated system.
How current is the UGV Beast data on ui44?
The UGV Beast specifications on ui44 were last verified on 2026-05-27. All data is sourced from official Waveshare documentation, spec sheets, and press releases. If you notice any outdated information, please let us know.
Data Integrity
All UGV Beast data on ui44 is verified against official Waveshare sources, including spec sheets, product pages, and press releases. Last verified: 2026-05-27. Official source: Waveshare product page. If you find outdated or incorrect information, please let us know — accuracy is our top priority.
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