Warehouse Mobile Target Localization Using Anchor Sub-Units
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Solution Overview
Problem
Existing localization methods for mobile targets in automatic warehouses face high installation costs and computational complexity due to the need for numerous fixed reference nodes, which increases with the number of targets and anchors, and struggles with error reduction and collision avoidance.
Innovation Solution
A method that divides the warehouse area into sub-units and uses asymmetrical distribution of anchors on an AGV to perform a two-step localization process, first making a rough estimation to select the relevant sub-units for an accurate position calculation using Time Difference of Arrival (TDoA) and multilateration/trilateration methods, reducing the number of anchors involved in each calculation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If numerous fixed reference nodes (anchors) are distributed in the warehouse environment, then localization coverage and reliability are improved, but installation costs and device complexity increase significantly
Solution Approach 1:
The patent segments the localization problem into two distinct phases: a rough localization phase using a limited number of anchors to determine the general area, and a precise localization phase using TDoA measurements from anchors in the identified sub-unit. This segmentation allows the system to achieve reliable localization without requiring numerous anchors throughout the entire warehouse, thereby reducing device complexity while maintaining reliability.
Solution Approach 2:
The patent introduces a hierarchical dimension to the localization process by first determining the sub-unit (spatial partition) and then performing precise positioning within that sub-unit. This dimensional approach allows the system to manage complexity by breaking down the large-scale warehouse into smaller manageable sub-units, each handled independently with fewer anchors.
2Measurement precision
If more anchors are used to reduce localization error, then measurement precision is improved, but computational complexity increases rapidly
Solution Approach 1:
The patent segments the set of all anchors into different groups based on their spatial distribution and relevance to the target's location. By performing rough localization first to identify the relevant sub-unit, the system only performs computationally intensive TDoA calculations using anchors from that specific sub-unit, rather than processing data from all anchors in the warehouse. This segmentation dramatically reduces computational complexity while maintaining high localization accuracy.
Solution Approach 2:
The patent applies partial action by using only the subset of anchors that are most relevant to the target's location (those in the identified sub-unit) for the precise localization calculation, rather than using all available anchors. This partial use of anchors reduces the computational burden significantly while still achieving the required measurement precision for collision avoidance.
3Measurement precision
If a centralized system processes all anchor measurements, then localization accuracy is maintained, but communication overhead and processing time increase
Solution Approach 1:
The patent segments the processing workload by first performing rough localization to identify the relevant sub-unit, then limiting subsequent precise localization calculations to only the anchors within that sub-unit. This segmentation reduces the volume of data that needs to be processed centrally, thereby reducing communication overhead and processing time while maintaining position estimation accuracy through the two-step approach.
4Reliability
If anchors are distributed throughout the warehouse, then collision avoidance reliability is improved, but installation cost increases
Solution Approach 1:
The patent segments the warehouse into multiple sub-units and strategically places anchors within each sub-unit rather than distributing them uniformly throughout the entire warehouse. The two-step localization process (rough localization followed by precise TDoA measurement within the identified sub-unit) ensures that collision avoidance reliability is maintained by focusing computational resources on the relevant local area, thereby reducing the total number of anchors needed while preserving safety.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enhances the accuracy and reliability of mobile target localization while reducing computational complexity and error, effectively avoiding collisions between AGVs and targets by focusing on specific sub-units of anchors for precise position estimation.
Implementation Method 1
a mobile target equipped with a signal emitter, an automatic guided vehicle (AGV) equipped with a plurality of anchors for receiving and, if desired, emitting signals
Implementation Method 2
perform a two-step localization process, first making a rough estimation to select the relevant sub-units for an accurate position calculation using Time Difference of Arrival (TDoA) and multilateration/trilateration methods
Data Source
AI summary
The present invention relates to a method for managing an automatic warehouse and for locating a mobile target, such as a person or a manual guided vehicle (1).