The operating system bringing AI into the physical world.
Deploy, monitor, and update fleets of Autonomous Mobile Robots (AMRs), AGVs, robotic manipulators, and physical AI systems from a single control plane. Native ROS 2 support, zero-copy shared memory, and complete hardware pass-through.
OS Footprint
Cold Boot
Failover Transport
What Admiral solves for autonomous robotics.
Bridging AI to bare-metal hardware
Robotics stacks require direct kernel-level access to motor controllers, CAN buses, and stereoscopic depth cameras. Containerizing them in traditional Docker causes latency jitter and broken device mapping.
Flaky roaming Wi-Fi in facilities
Moving robots constantly cross wireless access points in large warehouses and industrial sites, causing packet loss and connection drops that stall traditional cloud-dependent agents.
Safe field updates without bricking
Pushing navigation or autonomy model updates to machines actively operating near humans carries high risk. A failed update cannot leave a robot stuck in an inaccessible warehouse aisle.
Purpose-built for autonomous robotics.
Native ROS 2 & Zero-Copy /dev/shm
Unrestricted host networking for CycloneDDS and FastDDS multicast discovery, paired with sized tmpfs shared memory loaning for multi-gigabit camera and LiDAR point clouds.
Full Hardware Device Pass-Through
Direct access to /dev/ttyUSB* serial odometry, SocketCAN can0/can1 actuator buses, V4L2 cameras, and automatic Nvidia CUDA/TensorRT and Rockchip NPU driver mapping.
Docked Canary Rollouts & Auto-Rollback
Schedule phased canary deployments during base-station charging windows, with automated rollback if the updated workload fails health checks before starting its next mission.
With and without Admiral.
Without Admiral
- Opaque third-party daemons and bloated distro packages introduce supply-chain vulnerabilities
- Standard Linux distributions waste 1GB+ of RAM before robot nodes start
- Docker bridge networks break ROS 2 multicast and require brittle manual discovery scripts
- Shared memory copies choke CPU cores on 3D LiDAR and 4K stereo streams
- Failed updates brick vehicles in production aisles, requiring physical technician recovery
- Configuration drift across robot compute boards causes intermittent navigation bugs
With Admiral
- 100% compiled from source with zero vendor blobs or unvetted third-party packages
- Sub-10s boot times and ~100MB RAM footprint leave full compute for AI models
- Zero-copy POSIX shared memory removes perception serialization bottlenecks
- Host networking unlocks native DDS multicast discovery across on-chassis subnets
- Canary deployments stage safely while robots are docked at base chargers
- Automated rollback prevents machines from stranding in field aisles
Where autonomous robotics teams use Admiral.
Autonomous Mobile Robots (AMRs)
Manage warehouse fulfillment bots, dynamic path planners, and perception stacks across thousands of mobile chassis without configuration drift.
Automated Guided Vehicles (AGVs)
Orchestrate factory-floor transport vehicles, pallet movers, and industrial haulers with strict real-time scheduling guarantees.
Robotic Manipulators & Inspection Cells
Stream synchronized joint trajectories and visual quality inspection models to robotic arms with microsecond determinism.
Let's talk about your autonomous robotics fleet.
Start free with 5 devices or talk to our team to scope a production rollout.