Just-in-Time Model Update Protocol for Cyber-Physical Systems
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Solution Overview
Problem
Existing robotic systems face challenges in efficiently updating models to reflect changing environmental conditions, leading to inaccuracies and potential unsafe behaviors due to the high demand for computing resources and the introduction of delay times during updates.
Innovation Solution
The implementation of a just-in-time model update protocol that schedules updates only when necessary, using data structures and communication paths to reduce memory usage, CPU cycles, and network bandwidth, thereby optimizing resource demand and ensuring safe operation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If model updates are performed at a high rate to maintain accuracy, then model accuracy is improved, but computing resource consumption increases and delay time is introduced
Solution Approach 1:
The patent implements dynamic model update scheduling where the update rate is adjusted based on environmental conditions. The system monitors environmental parameters and dynamically determines when model updates are necessary, transitioning from static periodic updates to adaptive event-driven updates. This resolves the contradiction by making the update frequency dynamic rather than fixed, updating only when environmental changes warrant it.
Solution Approach 2:
The system changes the parameter of update frequency based on environmental conditions. When environmental parameters indicate significant changes, the update frequency increases; when conditions are stable, updates are reduced or paused. This parameter adaptation allows the system to maintain accuracy only when necessary, reducing overall computing resource consumption while preserving model validity.
2Measurement precision
If model updates are performed at a high rate to maintain accuracy, then model accuracy is improved, but delay time during updates increases
Solution Approach 1:
The patent implements dynamic model update scheduling where the update rate is adjusted based on environmental conditions. The system monitors environmental parameters and dynamically determines when model updates are necessary, transitioning from static periodic updates to adaptive event-driven updates. This resolves the contradiction by making the update frequency dynamic rather than fixed, updating only when environmental changes warrant it.
Solution Approach 2:
The system uses environmental sensor data to self-determine when model updates are needed, rather than relying on external scheduling or fixed intervals. The environmental conditions themselves trigger the update process, allowing the system to serve its own timing needs based on actual operational requirements, thereby minimizing unnecessary delay times.
3Use of energy by moving object
If model updates are performed infrequently to reduce computing resource consumption, then computing resource usage is reduced, but model accuracy deteriorates
Solution Approach 1:
The patent implements a feedback mechanism where environmental sensor data continuously monitors conditions that affect model accuracy. This feedback loop provides information about when environmental changes have occurred, triggering model updates only when necessary. The feedback from environmental sensors allows the system to maintain accuracy by updating in response to actual changes rather than on a fixed schedule, reducing unnecessary computing resource consumption.
4Measurement precision
If frequent model updates are performed to maintain accuracy, then model accuracy is improved, but network bandwidth usage increases
Solution Approach 1:
The system changes the parameter of update frequency based on environmental conditions. When environmental parameters indicate significant changes, the update frequency increases; when conditions are stable, updates are reduced or paused. This parameter adaptation allows the system to maintain accuracy only when necessary, reducing overall network bandwidth consumption while preserving model validity.
Data Source
AI summary
Methods and systems for parsimoniously updating cyber-system models based on then-current conditions. A wide variety of cyber-physical system models are deployed for ensuring that a system operates within its constraints while nevertheless achieving an assigned mission. Updating models is resource intensive, and thus should be done only when a particular degree of accuracy of a model is needed. Modern cyber-physical systems comprise sensors, transducers, and actuators that interoperate to carry out specific cyber-physical system behaviors. A control invariant barrier function (CBF) implements safety constraints that relate environmental parameters to safe behaviors of the cyber-physical system. Responsive to detected changes in the environment, a model update activity corresponding detected changes in the environment is initiated, but only when the result of such a model update impacts safe and/or mission-critical operation of the cyber-physical system. Invocation of model updates that would not impact safe operation of the cyber-physical system are suppressed.