Proof you can evaluate today
Architecture diagram
end-to-end stack overview (sensors → fusion → SLAM → planning)
Test snapshots
maps, trajectories, point clouds, failure cases & fixes
Benchmarks
latency / FPS / compute budget on edge hardware
Field notes
what worked, what didn’t, and what we changed (NDA-friendly)
Choose what you need: a full autonomy pipeline or specific modules. We design for constrained compute, harsh environments and real operational workflows.
- Perception
Multi-sensor perception using LiDAR, cameras and IMU — built for low-light and texture-poor interiors. - Localization & Sensor Fusion
Robust pose estimation with VIO/LiDAR/IMU fusion; resilient when GNSS is unavailable or jammed. - SLAM & Mapping
Real-time mapping, loop closure and exportable outputs for mission planning and documentation. - Planning & Control
Path planning, obstacle avoidance, speed profiles and terrain-aware behaviors. - Mission Logic & Safety
Failsafes, health monitoring, degraded-mode behavior, geofencing equivalents for indoor ops. - Integration Layer
MAVLink, ATAK-compatible workflows, payload interfaces, logging and data products.
- Indoor reconnaissance & inspection
Navigate corridors, shafts and complex building layouts and return with usable maps. - GPS-denied waypointing
Reliable movement when GNSS is unavailable: indoors, urban canyons, under canopy, in RF-heavy areas. - Autonomous exploration
Coverage-driven exploration that prioritizes safety, connectivity and return logic. - Digital twin capture (UGV)
Repeatable measurement runs to generate structured data for planning, documentation and decision-making.
A rugged UGV reference platform to validate perception, navigation and mapping workflows in real environments. Designed around edge compute and high-quality sensor stacks:
- Jetson-based edge compute
- LiDAR + 4K visual pipeline options
- Logging-first architecture for rapid iteration