Engineered for the edge cases
others design around
AXIOM's stack is built on a single continuous decision loop — perception, cognition, motion control, actuation, and fleet orchestration running in lockstep, entirely on-device. No cloud round-trip sits between a robot and a safety-critical decision.
Five layers, one continuous decision loop
Every AXIOM unit runs the full stack locally — from raw sensor fusion to actuation — and mesh-syncs with the fleet layer for coordination, not for control. That separation is what keeps latency low and uptime high at scale.
Subsystem specifications
Each subsystem is engineered, tested, and versioned independently — then validated as a whole against live warehouse conditions before any fleet-wide rollout.
Multi-modal sensor fusion
LiDAR, stereo vision, and thermal imaging fused at 40Hz into a unified occupancy model, with tactile and force feedback layered in for close-quarters manipulation.
Reactive path re-planning
Dynamic obstacle avoidance recomputes trajectories on-device without pausing throughput — trained against millions of logged warehouse-floor interactions.
Precision grasping
Force-feedback grippers adapt in real time to payload geometry and weight distribution, covering irregular SKUs without manual profile tuning.
Distributed task allocation
A self-healing mesh coordinates real-time task assignment across hundreds of units per site — with no single controller as a point of failure.
Redundant safety circuits
Dual-redundant e-stop paths, certified emergency braking, and continuous self-diagnostics run independently of the primary decision loop.
Fleet-wide model updates
Edge-collected interaction data trains updated perception and planning models nightly, validated in simulation before staged fleet rollout.
Why this architecture holds up at scale
These are the structural decisions that separate a lab demo from a fleet that runs 42 million hours without a controlling data center.
On-device inference
Safety-critical decisions never leave the unit. No cloud round-trip sits in the loop between sensing and stopping.
Self-healing fleet mesh
Coordination is peer-to-peer. Any single unit or gateway can drop out without stalling the rest of the fleet.
Continuous learning pipeline
Every unit contributes interaction data nightly; validated model updates roll out fleet-wide without floor downtime.
Modular hardware
Sensor payloads and end-effectors swap in the field without re-certifying the whole unit against safety standards.
See the architecture run in your facility
Walk through live telemetry, fleet dashboards, and the decision loop in action with our engineering team.