Inertial Sensor Initialization Using Soft Constraints
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing inertial sensor initialization methods require the sensor to be at rest or rely on additional sensor hardware, limiting their applicability in various conditions, especially where interrupting the sensor's operation or using extra hardware is impractical.
Innovation Solution
A method that estimates initial conditions of an inertial sensor using soft constraints and penalty metrics based on expected motion patterns during an initialization time interval, allowing for initialization without the need for the sensor to be at rest or supplemented with additional sensor data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the sensor is placed at rest in a known position and orientation for initialization, then the initialization process is simple and reliable, but the system cannot be used in continuous operation scenarios where interrupting the sensor is impractical
Solution Approach 1:
The system performs preliminary action by collecting sensor data during a specified initialization time interval before formal motion tracking begins. This preliminary data collection allows the system to estimate initial conditions (position, orientation, velocity) without requiring the sensor to be completely at rest, thus enabling initialization in continuous operation scenarios while maintaining reliability through pre-captured data.
Solution Approach 2:
The system applies dynamics by transitioning from static initialization requirements to dynamic initialization. Instead of requiring the sensor to be stationary, the system processes sensor data while the sensor is in motion during the initialization interval. The soft constraints are applied dynamically to moving sensor data to estimate initial conditions, making the system adaptable to continuous operation where the sensor cannot be stopped.
2Measurement precision
If additional sensor hardware (GPS, magnet) is used to supplement inertial sensor data for initialization, then absolute position and orientation can be determined, but the cost and complexity of the system increases
Solution Approach 1:
The inertial sensor system performs self-service by using its own sensor data to determine initial conditions without requiring external sensor inputs. The system processes accelerometer and gyroscope data during the initialization interval to estimate initial position, orientation, and velocity. This self-contained approach eliminates the need for additional GPS or magnet sensors, reducing hardware complexity and cost while maintaining the ability to initialize the system.
Solution Approach 2:
The inertial sensor is made multi-functional by enabling it to perform both motion tracking and initialization functions using the same hardware. The system processes sensor data in two different modes: during the initialization interval for determining initial conditions, and during motion tracking for measuring changes in position and orientation. This universal use of the inertial sensor eliminates the need for separate initialization hardware, reducing overall system complexity.
3Ease of operation
If the sensor is required to be at rest for initialization, then the initialization process is straightforward, but the system cannot be used in applications where the sensor must remain in continuous use
Solution Approach 1:
The system performs preliminary data collection during a specified initialization time interval before formal motion tracking begins. This preliminary action captures sensor data while the sensor is in use, allowing the system to estimate initial conditions without requiring the sensor to be stopped. The initialization process remains straightforward through automated processing of this preliminary data, while simultaneously enabling continuous use applications.
Solution Approach 2:
The system maintains continuity of useful action by allowing the sensor to remain operational during the initialization process. Instead of interrupting the sensor for a static initialization period, the system continuously collects and processes sensor data during the initialization interval. This continuous data collection enables both simple initialization through automated processing and adaptability to applications where the sensor must remain in continuous use.
Data Source
AI summary
An initialization method for an inertial sensor that estimates starting orientation and velocity without requiring the sensor to start at rest or in a well-known location or orientation. Initialization uses patterns of motion encoded as a set of soft constraints that are expected to hold approximately during an initialization period. Penalty metrics are defined to measure the deviation of calculated motion trajectories from the soft constraints. Differential equations of motion for an inertial sensor are solved with the initial conditions as variables; the initial conditions that minimize the penalty metrics are used as estimates for the actual initial conditions of the sensor. Soft constraints and penalty metrics for a specific application are chosen based on the types of motion patterns expected for this application. Illustrative cases include applications with relatively little movement during initialization, and applications with approximately periodic motion during initialization.