Multi-Sensor Motion Controller for Low-Drift Angular Rate Input
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Solution Overview
Problem
Existing angular rate sensors in human operable controllers suffer from noise, zero-rate drift, and scaling limitations, which affect the accuracy of control signals generated based on the angular rate of the controller, making them unsuitable for precise applications like VR, AR, and drone control.
Innovation Solution
The use of multiple sensors with different scales and sensor fusion techniques to measure and generate control signals, where each sensor is configured to optimal scales dynamically, and data from multiple sensors is averaged to reduce noise and zero-rate drift, enabling more accurate and continuous angular rate measurements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a single angular rate sensor is used to generate control signals, then the device complexity is low, but the measurement precision deteriorates due to noise, zero-rate drift, and scaling limitations
Solution Approach 1:
The patent combines multiple angular rate sensors with different scales into a single controller system. The processing circuitry integrates data from all sensors through averaging, creating a unified measurement system that achieves higher precision than any individual sensor could provide alone.
Solution Approach 2:
The patent changes the scale parameter of angular rate sensors to optimize measurements. By using sensors with different scales (e.g., full-scale ranges of 125 dps, 250 dps, 500 dps, 1000 dps, 2000 dps, 4000 dps), the system can adapt to various motion intensities and reduce quantization errors, thereby improving measurement precision across different operating conditions.
2Reliability
If multiple sensors with different scales are used to reduce noise and zero-rate drift, then the measurement precision improves, but the device complexity increases
Solution Approach 1:
The patent merges multiple sensor outputs through averaging in the processing circuitry. This combination approach reduces the impact of random noise and zero-rate drift by distributing measurement errors across multiple sensors, thereby improving reliability while maintaining a relatively simple implementation architecture.
Solution Approach 2:
The system uses the diversity of sensor scales as a self-service mechanism to automatically reduce errors. By averaging measurements from sensors with different full-scale ranges, the system inherently compensates for noise and drift without requiring complex calibration or correction algorithms, thus improving reliability with minimal additional complexity.
3Measurement precision
If sensors are configured to optimal scales dynamically, then the measurement precision improves for varying motion intensities, but the processing complexity increases
Solution Approach 1:
The patent implements dynamic scale configuration by selectively enabling or weighting sensors based on current motion intensity. Rather than continuously adjusting all sensor parameters, the system applies partial configuration changes by activating appropriate sensors for the current motion level, thereby improving precision without excessive processing overhead.
4Measurement precision
If data from multiple sensors is averaged to reduce noise, then the measurement accuracy improves, but the processing time increases
Solution Approach 1:
The patent combines sensor data through simple averaging in the processing circuitry, which is a computationally efficient operation. This approach achieves noise reduction and improved accuracy while minimizing processing time, as the averaging can be performed in real-time with minimal computational overhead compared to more complex filtering algorithms.
Data Source
AI summary
There is provided a human operable controller device and method for the controller device, wherein the controller comprises: a first sensor arrangement for measuring angular rate of the controller for at least one axis to provide a first measurement data; a second sensor arrangement for measuring angular rate of the controller for said at least one axis to provide a second measurement data; a processing circuitry for generating a control signal representing angular rate of the controller for said at least one axis based on the first measurement data and the second measurement data; and a communication interface for coupling with the external computer system and for providing the control signal to the external computer system to control the application.