Deterministic Distributed Control Architecture
A layered robotics control system that enforces deterministic actuation despite non-deterministic AI computation, using middleware validation, protocol abstraction, and isolated power domains.
Research thesis, system boundary, and motivation.
Deterministic Distributed Control Architecture
This research investigates how autonomous robotic systems can enforce safe, deterministic actuation while still using non-deterministic AI computation for perception, planning, and decision support.
The central hypothesis is that introducing a deterministic middleware layer between AI compute and actuator-facing controllers can bound command behavior, reject unsafe outputs, reduce timing risk, and improve system reliability.
The target domains are autonomous robotics, industrial automation, and space systems, where unsafe actuation cannot be treated as a normal software failure.
Current Limitation
Many robotics systems are structured around monolithic ROS-style pipelines where perception, planning, control, and actuation can become tightly coupled. This is useful for development velocity, but weak timing guarantees and direct actuator coupling create risk when high-level compute becomes delayed, overloaded, or unstable.
Proposed Direction
The architecture separates the system into layers:
- AI compute and planning
- Deterministic middleware validation
- Protocol-based actuation
- Isolated power distribution
Each layer has a narrow responsibility and measurable failure modes.