VSLAM Dynamic Object Filtering for Localization Stability
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Solution Overview
Problem
Existing visual simultaneous localization and mapping (VSLAM) methods for moving apparatuses, such as autonomous vehicles and drones, face instability and errors due to dynamic objects in the environment, leading to mapping misjudgments when returning to the same position at different times.
Innovation Solution
A localization and mapping method that includes image capturing, feature point extraction, flag object identification using a database of dynamic objects, and subsequent localization and mapping, which filters out dynamic objects to reduce errors and improve stability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional VSLAM methods are used to capture and process all feature points in the environment, then the localization and mapping can be performed, but the presence of dynamic objects causes mapping misjudgments and localization errors when returning to the same position at different time points
Solution Approach 1:
The patent extracts and identifies dynamic objects (flag objects) from the environment by comparing feature points across multiple image frames. By separating dynamic objects from static environment features, the system prevents dynamic objects from causing localization errors and mapping misjudgments, thereby resolving the contradiction between reliability and measurement precision
Solution Approach 2:
The patent performs preliminary identification and filtering of dynamic objects before conducting localization and mapping operations. By pre-processing the environment data to remove dynamic elements, the system ensures more accurate and reliable localization results when the apparatus returns to previously visited positions
2Measurement precision
If the system filters out dynamic objects to reduce localization errors, then the localization accuracy improves, but the complexity of the processing system increases due to the need for flag database and object identification
Solution Approach 1:
The patent implements a flag database that serves multiple functions: storing dynamic object information, enabling object identification, and supporting localization corrections. This multi-functional approach consolidates several processing tasks into a single system component, reducing overall system complexity while maintaining high localization accuracy
Data Source
AI summary
A localization and mapping method is for localizing and mapping a moving apparatus in a moving process. The localization and mapping method includes an image capturing step, a feature point extracting step, a flag object identifying step, and a localizing and mapping step. The image capturing step includes capturing an image frame at a time point of a plurality of time points in the moving process by a camera unit. The flag object identifying step includes identifying whether the image frame includes a flag object among a plurality of the feature points in accordance with a flag database. The flag database includes a plurality of dynamic objects, and the flag object is corresponding to one of the dynamic objects. The localizing and mapping step includes performing localization and mapping in accordance with the image frames captured and the flag object thereof in the moving process.