Event-Driven Vision Sensor Feedback for IMU Drift Correction
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing event-driven vision sensors lack sufficient consideration for their unique characteristics, hindering the improvement of IMU measurement accuracy and estimated values based on these sensors.
Innovation Solution
An electronic apparatus incorporating an event-driven vision sensor, an IMU, and a correction process that adjusts measurement results based on the frequency of event signals generated by the vision sensor to identify standstill states and correct errors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If event-driven vision sensor is used for high-speed operation and low power consumption, then operating speed and energy efficiency are improved, but measurement accuracy of IMU and estimated values deteriorate due to insufficient consideration of event-driven sensor characteristics
Solution Approach 1:
The system uses event signal frequency as feedback to dynamically adjust IMU measurement correction. The correction process section continuously monitors the frequency of event signals from the vision sensor and uses this information to correct IMU measurement results, creating a closed-loop feedback mechanism that resolves the accuracy issue while maintaining high-speed operation
Solution Approach 2:
The invention changes the parameter of measurement correction based on event signal frequency. By adjusting the correction amount according to the frequency of events detected by the vision sensor, the system adapts to varying operating conditions and maintains measurement accuracy across different speed regimes
2Device complexity
If event-driven vision sensor operates without considering its unique characteristics, then device simplicity is maintained, but measurement accuracy and reliability deteriorate
Solution Approach 1:
The invention merges the event-driven vision sensor with the IMU into an integrated measurement system. The correction process section combines data from both sensors, using event signal frequency to adjust IMU measurements, creating a unified system that leverages the strengths of both sensor types while compensating for their individual limitations
Solution Approach 2:
The correction process section acts as an intermediary between the event-driven vision sensor and the IMU. It receives event signals from the vision sensor, processes the frequency information, and uses this as a mediator to correct IMU measurement results, enabling reliable measurements without requiring complex direct integration
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enhances the accuracy of IMU measurement results and estimated values by identifying standstill conditions and canceling errors in the measurement data using the event-driven vision sensor's high-speed operation.
Implementation Method 1
a sensor array having a sensor that generates an event signal when detecting a change of an incident light intensity
Data Source
AI summary
Provided is an electronic apparatus including a vision sensor of an event-driven type including a sensor array having a sensor that generates an event signal when detecting a change of an incident light intensity, an inertial measurement unit (IMU) that is displaced together with the vision sensor, and a correction process section that corrects a measurement result from the IMU or an estimated value based on the measurement result from the IMU, according to the frequency of the event signals.