Autonomous Machine Sensor Assessment Using Collaborative Sensing
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Solution Overview
Problem
Autonomous machines face challenges in efficiently managing sensory failures, leading to increased downtime and maintenance efforts due to the complexity of their environments and the need for precise sensor reliability assessment.
Innovation Solution
Implementing a collaborative sensing and self-assessment method that allows autonomous machines to share sensing results and use assessment estimation models to determine sensor reliability, enabling real-time detection and minimization of sensory failures through peer comparison and adaptive maintenance strategies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If autonomous machines use complex sensor systems to operate in complex environments, then measurement precision and task capability improve, but device complexity and difficulty of detecting sensory failures increase
Solution Approach 1:
The patent introduces reference machines as intermediaries that provide benchmark sensing data. These reference machines serve as mediators between the complex sensor systems and the assessment process, enabling reliable sensor evaluation without directly increasing the complexity of each individual machine's sensor system. The reference machines establish a common reference framework that simplifies the assessment of sensor reliability across the autonomous machine fleet.
Solution Approach 2:
The patent creates virtual copies or models of sensing processes through reference machines. By copying the sensing functionality and comparing actual sensor outputs against these reference copies, the system can assess sensor reliability without adding physical complexity to the original sensor systems. This virtual replication enables comprehensive monitoring while maintaining system simplicity.
2Reliability
If autonomous machines perform continuous self-assessment of sensor reliability, then reliability of operation improves, but loss of time for assessment and processing increases
Solution Approach 1:
The patent implements preliminary assessment actions by continuously comparing current sensor data against pre-established reference data from reference machines. This ongoing preliminary comparison enables rapid detection of sensor failures without requiring time-consuming comprehensive assessments. The reference framework is prepared in advance, allowing for quick real-time evaluations that minimize assessment time while maintaining high reliability.
Solution Approach 2:
The system establishes continuous feedback loops where sensor data is constantly assessed and compared against reference values. This real-time feedback mechanism enables immediate detection of reliability issues without delaying operations. The feedback process is optimized to provide rapid assessments, ensuring that time loss is minimized while maintaining continuous monitoring of sensor reliability.
3Productivity
If autonomous machines operate without human intervention, then productivity increases, but loss of time due to sensory failures and downtime increases
Solution Approach 1:
The patent enables autonomous machines to perform self-assessment of their sensor reliability using reference machines and automated comparison algorithms. This self-service capability allows the machines to detect and respond to sensory failures independently without requiring human intervention, thereby maintaining high productivity while minimizing downtime. The system autonomously identifies issues and can trigger appropriate responses, ensuring continuous operation.
Solution Approach 2:
The system performs preliminary detection and assessment of sensor failures before they cause operational downtime. By continuously monitoring sensor reliability against reference standards, the system can identify potential failures early and take preventive actions, thereby avoiding complete system shutdowns and reducing overall downtime while maintaining autonomous productivity.
Data Source
AI summary
According to various aspects, a controller for an automated machine may include: one or more processors configured to: obtain a message from a further automated machine in accordance with a communication protocol, the message including a first result of a first sensing process that the further automated machine performs; and determine an assessment of the automated machine based on the first result and based on a second result of a second sensing process that the automated machine performs.