Self-position Estimation Using Dynamic Local Map Region Adjustment
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing self-position estimation systems for mobile bodies in dynamic environments often face challenges in accuracy and computational efficiency, particularly when dealing with varying landscapes and unknown obstacles, leading to potential errors in positioning and posture calculation.
Innovation Solution
The system employs a self-position estimating apparatus with a storage, local map generator, and adjuster, which generates and adjusts a local map to match environmental maps, allowing for precise positioning and posture estimation by adjusting the size of the local map disposing region based on predetermined conditions, thereby reducing computational load and estimation time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the image data detecting range is widened to improve self-position estimation accuracy, then more landmarks can be detected, but inappropriate self-position may be calculated when multiple similar landmarks are included
Solution Approach 1:
The patent applies local quality by adjusting the detecting range dynamically based on the local environment. When the mobile body is in a region with multiple similar landmarks, the detecting range is reduced to exclude ambiguous landmarks. When in a region with unique landmarks, the detecting range is expanded to improve accuracy. This localized adjustment of the detecting range resolves the contradiction between accuracy and reliability.
2Measurement precision
If the detecting range is unconditionally widened to include more landmarks, then self-position can be estimated from more data, but computation time and processing load increase
Solution Approach 1:
The patent implements dynamics by making the detecting range adjustable and adaptive rather than fixed. The range is dynamically modified based on environmental conditions detected during operation. When computation time is critical or landmarks are ambiguous, the range is reduced. When more data is beneficial and time permits, the range is expanded. This dynamic adjustment resolves the contradiction between accuracy and time.
3Reliability
If the detecting range is reduced to avoid similar landmarks, then appropriate self-position can be calculated, but fewer landmarks are available for estimation
Solution Approach 1:
The patent applies parameter changes by modifying the detecting range parameter based on environmental analysis. When similar landmarks are detected, the range parameter is reduced to improve reliability. When unique landmarks are present, the range parameter is increased to improve accuracy by including more landmarks. This conditional parameter adjustment resolves the contradiction between reliability and accuracy.
Data Source
AI summary
A self-position estimating apparatus includes a storage, a local map generator, a self-position estimator, and an adjuster. The storage stores an environmental map representing a position of an obstacle present in a mobile environment. The local map generator generates a local map representing a relative position of an obstacle present around the mobile body, with respect to the mobile body. The self-position estimator estimates, among a plurality of disposing positions on a local map disposing region set in the environmental map, one of the disposing positions where most exact matching is obtained between the local map and the environmental map, as a first self-position. The self-position estimator estimates a rotation angle of the local map at the disposing position as a first posture. The adjuster adjusts a size of the local map disposing region according to a predetermined condition.