Beacon Map Construction via Pose Constraint Graph Optimization
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Solution Overview
Problem
Existing beacon map construction methods using high-precision measuring equipment like total stations suffer from significant errors when switching stations, leading to reduced accuracy in robot positioning and navigation, especially in large environments.
Innovation Solution
A method involving iterative calculation and graph optimization to determine the accurate positions of beacons by establishing pose constraint relationships between station points and beacons, reducing error accumulation through precise measurement and correction of station point positions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If high-precision measuring equipment like total station is used to measure beacon positions, then measurement precision is improved, but device complexity increases and error accumulation occurs during station switching
Solution Approach 1:
The patent divides the large-scale measurement task into multiple station segments, where each station measures a portion of the beacons. By segmenting the measurement process and using graph optimization to integrate results from multiple stations, the system achieves high-precision beacon positioning without requiring a single complex measurement setup, thus resolving the contradiction between measurement precision and device complexity
Solution Approach 2:
The patent implements a feedback mechanism through graph optimization that processes measurement data from multiple stations, detects errors and inconsistencies, and iteratively corrects station positions and beacon coordinates. This feedback loop eliminates error accumulation during station switching while maintaining high measurement precision, resolving the contradiction between measurement accuracy and operational complexity
2Area of stationary object
If multiple station switching is performed to cover large scenes, then area of measurement is improved, but measurement precision deteriorates due to error accumulation
Solution Approach 1:
The patent transitions from traditional sequential station-to-station measurement to a multi-dimensional graph optimization approach. By representing measurement data as a graph structure with stations and beacons as nodes and measurements as edges, the system can simultaneously process data from multiple stations and solve for all positions in a unified mathematical framework, eliminating error accumulation while maintaining large-area coverage
Solution Approach 2:
The patent merges measurement data from multiple stations into a unified coordinate system through graph optimization. By combining observations from all stations and iteratively solving for consistent positions, the system achieves high-precision beacon mapping across large areas without the error accumulation that plagues traditional sequential measurement methods
Data Source
AI summary
A beacon map construction method, a device, and a computer-readable storage medium are provided. In the method, obtaining measured positions of beacons at the (i−1)-th station point by a measuring equipment; obtaining a first pose constraint relationship of the measuring equipment at the i-th station point relative to the (i−1)-th station point; obtaining a second pose constraint relationship of the i-th station point relative to beacons at the i-th station point, based on a pose of each of the beacons at the i-th station point, and the positions of the beacons at the (i−1)-th station point; determining an error equation of the i-th station point based on the first pose constraint relationship and the second pose constraint relationship; and optimizing the error equation to determine a position of the i-th station point, and constructing a beacon map based on the determined position of the i-th station point.