Mobile Platform Sensor Redundancy Switching
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Solution Overview
Problem
Current mobile platforms, such as unmanned aerial vehicles (UAVs), face reliability and safety issues due to malfunctions, leading to accidents like crashes and collisions, as existing systems fail to effectively detect and mitigate sensor malfunctions in real-time.
Innovation Solution
A method and apparatus for operating mobile platforms that involve selecting a secondary sensor with lower weight to communicate with the sensor controller upon detecting a malfunction in the primary sensor, ensuring continuous operation by switching to a redundant sensor that generates the same data type, thereby preventing accidents and improving safety.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a single primary sensor is used for data collection, then the system structure is simple, but the reliability deteriorates when the sensor malfunctions
Solution Approach 1:
The patent applies preliminary action by pre-configuring multiple sensors and establishing a statistical weight function before any malfunction occurs. The system proactively prepares redundant sensors and pre-determines their weights for potential use, so that when a malfunction happens, the switch to backup sensors can occur immediately without complex real-time decision-making, thus improving reliability while keeping the switching mechanism relatively simple
Solution Approach 2:
The patent employs parameter changes by dynamically adjusting the statistical weights of different sensors based on their performance and reliability metrics. When a sensor malfunctions, its weight is adjusted to zero or excluded from the calculation, and the system reweights the remaining sensors. This parameter-based approach allows flexible adaptation to sensor failures without requiring complex structural changes to the sensor system
2Reliability
If multiple sensors with different weights are used, then the reliability improves through redundancy, but the device complexity increases
Solution Approach 1:
The patent implements feedback by continuously monitoring sensor performance and using the statistical weight function to evaluate sensor quality. The system receives feedback from sensor data, compares it against expected patterns, and automatically adjusts sensor weights based on detected anomalies or malfunctions. This closed-loop feedback mechanism enables the system to adapt to sensor failures dynamically, improving reliability while managing complexity through automated rather than manual sensor management
Solution Approach 2:
The patent applies universality by designing a unified statistical weight function that can evaluate and manage multiple different types of sensors (e.g., GPS, compass, accelerometers) through a common framework. This multi-functional approach allows the same weighting mechanism to handle various sensor types and failure modes, reducing the need for separate management systems for each sensor type and thereby controlling overall system complexity
3Reliability
If real-time sensor malfunction detection is implemented, then the safety improves, but the processing time and computational load increase
Solution Approach 1:
The patent applies preliminary action by pre-establishing the statistical weight function and sensor hierarchy before any malfunction occurs. The system pre-determines which sensors are primary, secondary, or tertiary based on their reliability characteristics. When a malfunction is detected, the system can immediately switch to pre-identified backup sensors without needing to calculate optimal sensor combinations in real-time, significantly reducing detection and switching time while maintaining high safety standards
Data Source
AI summary
A method for operating a mobile platform includes detecting a malfunction in a first sensor communicating with a sensor controller associated with the mobile platform, and, in response to detecting the malfunction in the first sensor, eliminating the first sensor from a sensor data source for controlling the mobile platform, enabling a second sensor to be in the sensor data source, continuing to receive and evaluate data from the first sensor, and, in response to not detecting an anomaly in the data from the first sensor, restoring the first sensor back into the sensor data source.