RoboFacetRoboFacet

Large research UGV for outdoor payload integration

Product information

Information below comes from the product website or public documentation. Pricing and availability may change.

Category
Robot Development
Maturityi
Not specified
Deploymenti
Physical hardware
Buying / access
Contact the vendor for pricing
Source
Official websiteChecked Oct 10, 2026

Key specifications

Sources are linked in the table. Select a specification for its meaning and buying context.

Land speed; exact km/h-to-m/s conversion.

Robot body weight

280 kg

Includes battery pack.

External dimensions

1.52 × 1.38 × 0.83 m

Ground clearance

254 mm

Official product pageSource accessed Oct 10, 2026

Specifications are compiled from the linked manufacturer-published sources and may vary by model, configuration or region. Confirm the latest manufacturer documentation before purchase.

Reality check

A demo shows what may be possible. These points help judge whether the product fits day-to-day use.

Works well when
  • Simulation, control, perception and repeatable experiments
  • Teams that can manage dependencies and hardware interfaces
  • Prototyping before committing to a physical deployment
What to check
  • Supported hardware, GPU requirements and version compatibility
  • Documentation, examples and community response
  • How simulation results transfer to the real robot
Not a magic solution
  • A guarantee that simulation equals a production cell
  • A replacement for safety validation on hardware
  • A low-maintenance toolchain without version ownership

About

Warthog is an outdoor development platform for agriculture, mining and inspection prototypes. It lists 272 kg maximum payload, 280 kg base weight including batteries and 18 km/h land speed. Mounting plates, accessible power and ROS 2 interfaces support integration of sensing and manipulation equipment.

Product details

Manufacturer / team
Clearpath Robotics
Product typei
Platform
ROS / ROS 2 supporti

The cost iceberg

The purchase price is only one part of an automation project.

GPU, simulation assets and hardware adapters
Dependencies, datasets and test infrastructure
Version pinning, documentation and support
Sim-to-real gaps and safety validation

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