Inertial Sensor State Estimation for Positioning Reliability
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Solution Overview
Problem
Autonomous positioning using inertial sensors suffers from cumulative errors over time, leading to unreliable detection of user position, particularly when calibration is not performed during prolonged movement, which can result in navigation errors such as getting lost.
Innovation Solution
An information processing apparatus and method that estimates the state of an object using inertial sensors and controls the output of reliability information based on the estimated state, performing calibration when conditions are met, such as during standstill or adequate GNSS signal intensity, to correct zero-point biases and maintain accurate positioning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Duration of action of moving object
If autonomous positioning is performed using inertial sensors without frequent calibration, then the device can operate continuously without interruption, but cumulative errors increase over time leading to reduced positioning reliability
Solution Approach 1:
The system performs calibration periodically when specific conditions are met (e.g., when the device is detected to be stationary or when GNSS signals become available). This periodic calibration resets cumulative errors while allowing continuous operation between calibration events, resolving the contradiction between continuous operation and positioning reliability.
Solution Approach 2:
The system continuously monitors operational conditions (stationary detection, GNSS signal availability) and uses this feedback to determine when calibration should be performed. This feedback mechanism ensures calibration occurs at appropriate times to maintain reliability without interrupting continuous operation.
2Reliability
If calibration is performed frequently to maintain positioning accuracy, then reliability of detection position is improved, but operation is interrupted and user convenience is reduced
Solution Approach 1:
Instead of frequent periodic calibration, the system uses event-triggered calibration that occurs only when specific conditions are met (stationary state, GNSS availability). This reduces calibration frequency while maintaining reliability, improving user convenience without sacrificing positioning accuracy.
Solution Approach 2:
The system automatically performs calibration when conditions permit without requiring user intervention or awareness. This self-service approach maintains reliability while avoiding interruptions that would reduce user convenience, as users are not notified or required to initiate calibration manually.
3Measurement precision
If calibration is delayed until the device is stationary, then measurement precision can be improved, but time loss occurs when the device remains in motion
Solution Approach 1:
The system prepares for calibration by continuously monitoring conditions (detecting stationary states, monitoring GNSS signal strength) in advance. When calibration opportunities arise, they are seized immediately, minimizing the time without calibration while ensuring measurement precision is maintained through proper timing.
Solution Approach 2:
The system uses feedback from condition monitoring (stationary detection, GNSS availability) to trigger calibration at the optimal moment. This feedback-driven approach ensures calibration occurs when measurement precision can be achieved without excessive time loss, balancing both requirements dynamically.
Data Source
AI summary
The present technology relates to an information processing apparatus and an information processing method that make it possible to properly report the reliability of information that is available with use of an inertial sensor. The information processing apparatus includes a state estimation section that estimates a state of a predetermined object and an output controller that controls, on the basis of the estimated state of the object, output of reliability information indicating the reliability of object information of the object, the object information of the object being available with use of an inertial sensor. The present technology is applicable to a portable information terminal such as a smartphone or a wearable device, for example.