RVPU vision for ground & mobile platforms
Configurable vision for robots that work where the network does not.
Visual SLAM assistance, person/object detection, sensor fusion, and AMR scene parsing — pre-compiled pipelines running on-platform on an AMD Kria KV260. Select a pipeline, point it at your camera, and outputs land in ROS 2. No tethered GPU. No cloud round-trip. No AI or FPGA team.
Use cases
Where on-platform vision earns its keep
Visual SLAM assistance
Visual-inertial odometry and SLAM assistance running on-platform with deterministic latency — no offloading to a chase vehicle.
Person & object detection
Detect and classify people and objects on-device, in real time, with the pipeline feeding your planner directly over ROS 2.
Multi-sensor fusion
Fuse camera and depth streams into one on-device scene representation — detection, segmentation, and tracking without a downlink.
AMR scene parsing
Parse the scene for navigation, planning, and manipulation, and hand structured perception to the rest of your autonomy stack.
Comms-denied autonomy
Perception stays on the robot when the link drops. No degradation when the uplink does — resilient in contested environments.
Sovereign & resilient
Sovereign supply and defense-grade posture — deployable under any country’s sovereignty requirements, with hardware root of trust, signed firmware, per-module attestation, and a forensic trace buffer. Designed for MIL-STD-810H environments — qualification on the roadmap.
The matched RVPU
TerraBot X
RVPU · ground robotics · Kria KV260
TerraBot X is an RVPU appliance on an AMD Kria KV260, built for ground robots, mobile platforms, and AMRs. Select a pipeline — visual SLAM assistance, person/object detection, sensor fusion, or AMR scene parsing — point it at your camera, and outputs land natively in ROS 2. Perception runs on-platform and keeps working when the link drops.
- Platform
- AMD Kria KV260
- Pipelines
- Ground-robotics vision suite
- Integration
- ROS 2 · MAVLink
- Operating range
- −40 to +85 °C target
Why this module, this vertical
The properties that map to your platform.
Pipelines, not models
The RVPU ships pre-compiled, configurable computer-vision pipelines — stereo depth, object detection, EO/IR tracking, gimbal-stabilized detection. Select a pipeline and point it at your camera. No model code, no AI engineering.
Vision-specific by design
Built for robotics perception, not repurposed from a general-purpose accelerator. Bitstream switching lets a platform reconfigure its pipeline mid-mission for the task in front of it.
ROS 2 & MAVLink native
Pipeline outputs land directly in your robotics and flight stacks. First-class ROS 2 and MAVLink integration means the RVPU drops into an existing autonomy pipeline without glue code.
Secure by design, forensic by default
Hardware root of trust, signed firmware, and per-module attestation keep the device tamper-evident. An 8,192-entry cycle-accurate hardware trace buffer gives forensic-grade observability for mission review and ROE compliance.
Invotet SDK
Configure a pipeline. Deploy it to the RVPU.
A Python SDK for configuring and deploying pre-compiled vision pipelines to the RVPU — describe your camera, pick a pipeline, and stream outputs to ROS 2 and MAVLink. It ingests PyTorch, ONNX, and HuggingFace models when a pipeline needs a custom detector, with no CUDA in the loop. App config, not model code.
Framework
PyTorch
Bring a custom detector: trace or torch.export models fold into a pipeline with no rewrite.
Framework
ONNX
Standards-based interchange — any ONNX-exported model can back a pipeline stage.
Framework
HuggingFace
Vision checkpoints load through a one-line loader when a pipeline is customised.
Talk to the team behind the RVPU.
Most robotics conversations start with your camera and your autonomy stack. Tell us what your robot has to see and we will set up a TerraBot X evaluation through the design-partner program and route the right documentation.