Score Gradient Mapping for Mobile Body Self-Position Estimation
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Solution Overview
Problem
Existing technologies for autonomous mobile bodies struggle to accurately estimate their self-position due to limitations in calculating self-position estimation easiness parameters, which are often based solely on obstacle shape complexity, leading to inconsistent estimation accuracy.
Innovation Solution
An information processing device that acquires first map information and sensor information to generate a score gradient map indicating the score change rate, which represents the matching degree between the map and sensor information, thereby improving self-position estimation accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If self-position estimation easiness parameter is calculated based solely on obstacle shape complexity, then calculation is simple, but estimation accuracy of self-position cannot be consistently improved
Solution Approach 1:
The patent changes the parameter used for self-position estimation from simple obstacle shape complexity to a comprehensive score change rate that incorporates multiple factors including map matching degree, sensor information consistency, and environmental features. This parameter transformation enables consistent improvement in estimation accuracy while maintaining computational feasibility through systematic evaluation criteria.
2Measurement precision
If comprehensive map matching is performed to improve estimation accuracy, then self-position estimation accuracy improves, but processing time and computational load increase
Solution Approach 1:
The patent performs preliminary actions by pre-processing map information and sensor data to extract key features and generate score change rate maps in advance. This allows the system to quickly compare pre-computed score change rates with current sensor readings, significantly reducing real-time processing time while maintaining high estimation accuracy through comprehensive matching.
Data Source
AI summary
An information processing device includes an acquisition unit that acquires first map information concerning a first map corresponding to a moving environment of a mobile body, the first map being generated in advance, and sensor information of the mobile body at positions in the moving environment and a generation unit that generates second map information concerning a second map indicating a score change rate indicating a matching degree between the first map information and the sensor information, the change rate being the score change rate at the positions in the moving environment.