Onboard Object Detection
Real-time AI inference at 10.5 Mpx/s on resource-constrained platforms. YOLOX optimized for space-grade hardware.
Deploy state-of-the-art object detection on resource-constrained space platforms. Our solution brings YOLOX performance to radiation-tolerant FPGAs, enabling autonomous decision-making at the edge.
Developed under armasuisse S+T contract, this capability has been demonstrated on Xilinx UltraScale+ MPSoC — a platform pathway to space-grade Versal devices.
Performance
Key Features
Quantization-Aware Training
INT8 quantization with minimal accuracy loss. Optimized for FPGA inference engines.
Custom Dataset Support
Train on your mission-specific objects. End-to-end pipeline from data curation to deployment.
FPGA Acceleration
Vitis AI integration for Xilinx devices. Pathway to radiation-hardened Versal processors.
Real-Time Processing
Frame-by-frame inference for autonomous operations. No ground-in-the-loop required.
Use Cases
Space Situational Awareness
Detect and track objects in orbit for collision avoidance and space surveillance.
Earth Observation
Onboard detection of features of interest for selective downlink or autonomous response.
Rendezvous & Proximity
Real-time target detection for autonomous docking and servicing missions.
Technology Stack
Model
- YOLOX-Nano
- INT8 quantized
Training
- PyTorch
- Vitis AI
Hardware
- Xilinx UltraScale+
- Xilinx Versal
Integration
- Linux / PetaLinux
- Bare-metal option
Heritage
armasuisse S+T Project
DemonstratedDeveloped and demonstrated under armasuisse Science and Technology contract. Proven on representative flight-like hardware.
Interested in Onboard AI?
Contact us for technical discussions or demonstration opportunities.