Distributed Filter System for Mobile Robot Localization
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Solution Overview
Problem
Conventional localization technologies for mobile robots with a single filter structure face challenges in accuracy and robustness due to increased complexity and calculation load as the number of sensors grows, leading to potential filter divergence and difficulty in recovering from errors.
Innovation Solution
A distributed filter system comprising multiple local filters and a fusion filter that integrates relative and absolute position information, using sensors like cameras and IMUs to improve localization accuracy and convergence, with a preprocessing unit for node recognition and uncertainty removal.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple sensors are installed to improve localization accuracy, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent divides the single filter structure into multiple independent local filters, each processing information from specific sensors. This segmentation allows each filter to handle a subset of sensor inputs independently, reducing the complexity burden on any single filter while maintaining overall localization accuracy through coordinated operation of multiple filters.
2Measurement precision
If multiple sensors are installed to improve localization accuracy, then measurement precision is improved, but calculation load increases
Solution Approach 1:
The patent segments the calculation load by distributing sensor information processing across multiple independent local filters. Each filter processes a portion of the sensor data independently, reducing the computational burden on any single processing unit and enabling parallel execution, thereby lowering overall calculation load while maintaining high localization accuracy.
Solution Approach 2:
The patent implements multiple local filters that each perform partial localization calculations independently. Rather than one filter processing all sensor inputs comprehensively, multiple filters perform partial processing on subsets of data, and their results are integrated. This partial action approach distributes computational effort and reduces the excessive calculation load on any single filter.
3Ease of operation
If a single filter structure is used to simplify implementation, then ease of operation is improved, but reliability decreases
Solution Approach 1:
The patent segments the filter system into multiple independent local filters, each with its own processing logic and sensor inputs. This segmentation provides redundancy and independence, so that if one filter malfunctions or receives defective sensor information, other filters can continue operating independently, thereby improving overall system reliability while maintaining implementation simplicity through modular design.
Solution Approach 2:
The patent prepares multiple independent local filters in advance, creating a redundant system structure before operation. This beforehand cushioning ensures that if one filter fails or receives defective input, the system already has other functional filters ready to compensate, thereby improving reliability without complicating the operational implementation of individual filters.
4Ease of operation
If a single filter processes all sensor information, then ease of operation is improved, but localization accuracy deteriorates
Solution Approach 1:
The patent segments sensor information processing across multiple local filters, with each filter specialized for processing specific sensor inputs or types of localization data. This segmentation allows each filter to optimize its processing for particular sensor characteristics, improving overall localization accuracy while maintaining operational simplicity through the modular and coordinated structure of multiple independent filters.
Data Source
AI summary
A mobile apparatus and a localization method thereof which perform localization of the mobile apparatus using a distributed filter system including a plurality of local filters independently operated and one fusion filter integrating results of localization performed through the respective local filters, and additionally apply accurate topological absolute position information to the distributed filter system to improve localization performance (accuracy, convergence and speed in localization, etc.) of the mobile apparatus on a wide space. The mobile apparatus includes at least one sensor, at least one first distribution filter generating current relative position information using a value detected by the at least one sensor, at least one second distribution filter generating current absolute position information using the value detected by the at least one sensor, and a fusion filter integrating the relative position information and the absolute position information to perform localization.