Robot Safety Module Using Stimulus-Response Integrity Checks
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Solution Overview
Problem
Current safety monitoring methods for robots are primarily reactive, detecting malfunctions only after they pose a danger to human safety or cause damage, rather than proactively identifying and addressing safety and integrity violations in real-time.
Innovation Solution
The implementation of a duplex federated learning-based safety system that uses stimulus-response pairs to assess robot integrity and detect anomalies, allowing for proactive intervention and self-healing mechanisms to prevent safety violations, employing a combination of anomaly detection and integrity preservation techniques through machine learning and reinforcement learning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If reactive safety monitoring methods are used to detect malfunctions, then the system complexity is reduced, but the safety detection capability is insufficient as malfunctions are only detected after they pose a danger
Solution Approach 1:
The patent implements preliminary safety assessments by continuously monitoring robot operations against safety criteria before malfunctions can cause harm. The system proactively identifies potential safety issues by comparing actual robot behavior with expected safe operation patterns, enabling intervention before dangerous situations arise.
Solution Approach 2:
The patent establishes a feedback mechanism where safety monitoring data is continuously analyzed and used to adjust robot operations in real-time. The system provides feedback loops that allow the robot to self-correct potential safety violations by comparing its state against safety criteria and making adjustments before malfunctions occur.
2Reliability
If proactive safety assessment systems are implemented to detect safety violations in real-time, then the safety detection capability is improved, but the system complexity increases
Solution Approach 1:
The patent creates a universal safety monitoring framework that can assess multiple types of safety violations across different robot operations using a single integrated system. The safety criteria and assessment mechanisms are designed to be applicable across various robot functions and environments, reducing the need for separate specialized monitoring systems for each operation type.
3Reliability
If continuous safety monitoring is performed to prevent malfunctions, then the reliability is improved, but the productivity may be reduced due to potential interference with primary tasks
Solution Approach 1:
The patent implements partial monitoring by focusing safety assessments on critical operations and parameters that pose the greatest safety risks, rather than continuously monitoring all robot functions at full intensity. The system adjusts the level of monitoring based on the current operational context, applying more rigorous assessment only when necessary to maintain safety while minimizing interference with normal operations.
Data Source
AI summary
A safety system includes a robot, the robot comprising, a function module, configured to perform a robot function; anda safety module, configured to communicate with the robot, the safety module comprising a stimulus-response tester, configured to send a stimulus of a stimulus-response pair, comprising a stimulus and an expected response to the stimulus, to the robot for processing by the function module; and receive from the function module a response representing the processed stimulus; wherein if a difference between the response and the expected response is within a predetermined range, the safety module is configured to operate according to a first operational mode; and if the difference between the response and the expected response is outside of the predetermined range, the safety module is configured to operate according to a second operational mode.