SLAM Bias Compensation for Accurate Moving Distance Estimation
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Solution Overview
Problem
Current SLAM methods face challenges in accurately calculating the moving distance of movable objects due to biases in linear velocity measurements, which affect the precision of state information updates in Simultaneous Localization and Mapping processes, particularly in autonomous vehicle applications.
Innovation Solution
An electronic apparatus and method that acquires information on linear and rotational velocities of movable objects, calculates their moving distance and rotation angle, and updates SLAM state information by considering a bias identified based on the linear velocity, using a processor to model and subtract the bias, thereby improving accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If linear velocity measurement is used to calculate moving distance in SLAM, then the calculation process is simple, but measurement precision deteriorates due to bias in velocity measurements
Solution Approach 1:
The patent implements feedback by continuously monitoring the bias in linear velocity measurements and using this information to correct subsequent distance calculations. The system estimates bias based on observed deviations and feeds this correction back into the SLAM algorithm, improving measurement precision while maintaining calculation simplicity.
Solution Approach 2:
The patent changes the parameter approach by transitioning from using raw linear velocity measurements directly to using bias-corrected velocity values. This parameter transformation allows the system to maintain the simplicity of the calculation process while significantly improving the precision of moving distance measurements through bias compensation.
2Measurement precision
If bias correction based on linear velocity is implemented, then moving distance calculation precision is improved, but device complexity increases
Solution Approach 1:
The patent introduces an intermediary bias estimation component that mediates between the simple linear velocity measurement and the final distance calculation. This intermediary layer processes the velocity data to extract and correct bias, improving precision without requiring complete redesign of the calculation process, thus limiting the increase in complexity.
3Measurement precision
If state information is updated frequently for accurate SLAM, then localization accuracy is improved, but loss of time increases due to repeated calculations
Solution Approach 1:
The patent applies partial action by updating state information selectively rather than continuously. The system identifies key moments when updates are most beneficial and performs calculations only at those points, reducing the time loss from repeated calculations while maintaining sufficient localization accuracy for practical applications.
Data Source
AI summary
A method of calculating a moving distance of a movable object in consideration of a bias identified based on a linear velocity of the movable object in the process of implementing a SLAM, and an electronic apparatus therefor are provided. One or more of an electronic apparatus, a vehicle and an autonomous vehicle disclosed in the present invention may be connected to an artificial intelligence module, a drone (Unmanned Aerial Vehicle, UAV), a robot, an augmented reality (AR) device, a virtual reality (VR) device, a device related to 5G service, and so on.