Factory Object Mapping With Multi-Sensor Grouping to Cut Latency
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Solution Overview
Problem
Current methods for creating object maps in factory environments face challenges with latency issues when combining information from multiple sensors, which affects the precision and efficiency of determining object positions, particularly in large or complex settings.
Innovation Solution
A method utilizing multiple sensors to record and transmit information to a high-performance server for processing, allowing for the creation of precise object maps by combining data from various sensors, including cameras, LIDARs, and other devices, with the ability to update maps continuously and control devices based on accurate position data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If information from multiple sensors is combined to determine object positions, then measurement precision is improved, but latency time increases
Solution Approach 1:
The system segments the sensor network into multiple groups, with each group assigning a specific sensor as master and others as slaves. The master sensor performs initial processing and transmits data to a server, while slave sensors transmit only when objects are detected within their fields. This segmentation reduces overall data transmission volume and processing latency while maintaining position determination precision through coordinated multi-sensor coverage.
Solution Approach 2:
Master sensors perform preliminary processing of sensor data before transmitting to the server. The system pre-establishes communication protocols and data formats, and master sensors pre-filter and organize data from slave sensors before transmission. This preliminary action reduces the processing burden on the server and accelerates overall position determination, reducing latency while maintaining precision.
2Measurement precision
If multiple sensors record information about object positions, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The sensor network is segmented into master-slave groups, simplifying the overall system architecture. Each group has a designated master sensor that coordinates communication and data processing, reducing the complexity of inter-sensor communication protocols while maintaining the precision benefits of multiple sensors through structured organization.
Solution Approach 2:
Slave sensors within each group are merged under the coordination of a master sensor. The master sensor aggregates data from multiple slave sensors and manages communication with the server, effectively combining the functionality of multiple sensors while presenting a simplified interface. This merging reduces communication overhead and simplifies the network architecture while preserving multi-sensor measurement precision.
Data Source
AI summary
The disclosure relates to a method for creating an object map for a factory environment by using sensors present in the factory environment, wherein at least one part of an object in the factory environment has information relating to its position recorded by at least two of the sensors, wherein the information recorded by the sensors is transmitted to a server associated with the sensors, and wherein the server is used to take the information recorded and transmitted by the sensors as a basis for creating an object map for the factory environment having a position of the at least one part of the object.