01
Autonomy bounded by physical safety
Keep adaptive perception and planning inside deterministic limits, independently enforceable stops and accountable operating procedures.
Industry / RA
Autonomous systems engineered for the operating floor—not the demonstration floor.
Commercial robots operate inside changing physical environments where perception quality, control latency, human behaviour and equipment condition cannot be treated as fixed inputs.
Operating context
Technology has to fit the institution around it.
Commercial robots operate inside changing physical environments where perception quality, control latency, human behaviour and equipment condition cannot be treated as fixed inputs.
The engineering objective is a complete operating system: dependable autonomy, explicit safety boundaries, fleet observability and a maintainable path from field evidence back into software improvement.
Operating agenda
Priorities that shape the architecture.
We translate operating risk and commercial objectives into explicit system boundaries, evidence and decision ownership.
02
Fleet reliability beyond a single prototype
Standardise configuration, telemetry, release control and recovery so each deployed unit does not become a separate experiment.
03
Useful work measured at system level
Evaluate cycle time, intervention rate, availability and process outcome—not an isolated perception benchmark.
Engineering contribution
Where Root Digit contributes.
Each engagement is scoped around a real operating decision, a controlled technical boundary and evidence that leadership can review.
RA.1
Robot autonomy
Perception, localisation, planning and control integrated around the real operating environment.
- ROS 2 and real-time systems
- Navigation and manipulation
- Multi-sensor perception
RA.2
Fleet and mission operations
Software for dispatch, coordination, monitoring and controlled remote intervention.
- Mission orchestration
- Fleet observability
- Human intervention workflows
RA.3
Simulation and verification
Repeatable environments for scenario coverage, regression testing and system integration.
- Digital environments
- Software and hardware in the loop
- Scenario and safety regression
RA.4
Operational integration
Interfaces joining robots to production, warehouse, inspection and maintenance workflows.
- Enterprise and plant integration
- Workcell and facility interfaces
- Deployment and support tooling
Control plane
Controls designed with the system.
Assurance is part of the architecture and operating model—not a review added after delivery.
01
Independent safety
Hazardous motion is bounded by safety-rated functions outside learned behaviour.
02
Configuration control
Software, calibration, maps and hardware variants remain attributable by unit.
03
Degraded behaviour
Loss of sensing, positioning, network or compute leads to defined and tested states.
04
Field evidence
Interventions, near misses and failure modes return to a governed improvement loop.
Practical entry points
Start with one decision that matters.
01
Prove one operating mission
Define the task, environment, hazards and intervention budget before choosing autonomy.
02
Stabilise a prototype fleet
Introduce release control, observability and common configuration across deployed units.
03
Build a verification environment
Turn critical field scenarios into repeatable software and hardware tests.
Continue exploring
Related capabilities and evidence.
Industry conversation