Warehouse Fleet Control Using Context Models and Unified Data Streams
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Solution Overview
Problem
In industrial environments like warehouses, manual or static automated control of mobile industrial trucks and infrastructure objects leads to inefficiencies due to the need for numerous interfaces and sensors, and requires complex operator intervention, especially in dynamic settings.
Innovation Solution
A data processing device with a communication interface and processor that receives and processes multiple data streams from trucks, robots, and infrastructure objects, using a context model, such as a digital twin or machine learning model, to generate control signals for efficient movement and regulation, reducing the need for manual planning and training.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automated control systems are used for mobile industrial trucks, then productivity is improved, but device complexity increases due to the need for numerous interfaces and sensors
Solution Approach 1:
The patent combines multiple data streams from various sources (sensors, interfaces, control systems) into a unified data processing architecture. The central processing unit aggregates information from numerous interfaces and sensors, processing them collectively to generate control signals, thereby reducing the effective complexity despite maintaining comprehensive automation capability.
Solution Approach 2:
The control system is designed as a universal platform that can handle multiple types of data streams from different sources (mobile industrial trucks, infrastructure objects, sensors) through a single integrated processing unit. This multi-functional approach allows the system to manage diverse inputs and outputs without requiring separate specialized systems for each function.
2Ease of operation
If static automated control is used, then ease of operation is improved, but adaptability deteriorates in dynamic warehouse environments
Solution Approach 1:
The control system transitions from static to dynamic operation by continuously receiving and processing real-time data streams from the warehouse environment. The system adapts its control signals based on current conditions, allowing it to respond dynamically to process disruptions while maintaining ease of operation through automated decision-making.
Solution Approach 2:
The system implements continuous feedback loops by receiving data streams from sensors and control objects, processing this information, and generating updated control signals. This feedback mechanism enables the system to adapt to changing conditions in real-time while maintaining simple automated operation without requiring extensive operator intervention.
3Measurement precision
If extensive sensor installation is used for comprehensive control, then measurement precision is improved, but ease of manufacture deteriorates due to installation effort
Solution Approach 1:
The system uses a universal data processing platform that can handle multiple types of sensor inputs through a single architecture. This allows comprehensive environmental monitoring with multiple sensor types while simplifying installation, as the unified system can accommodate various sensor configurations without requiring separate processing systems for each sensor type.
Data Source
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AI summary
The invention relates to a device (110), in particular a data processing device (110), for controlling and/or regulating a plurality of industrial trucks (120a), industrial robots and/or automated infrastructure objects (120b) in an industrial environment, in particular a warehouse. The data processing device (110) comprises a communication interface (113) configured to receive a plurality of data streams, each of which comprises data acquired in the industrial environment, in particular in the warehouse, from the plurality of industrial trucks (120a), industrial robots and/or automated infrastructure objects (120b).Furthermore, the data processing device (110) comprises a processor unit (111) configured to generate a multitude of signals for controlling and/or regulating the multitude of industrial trucks (120a), industrial robots, and/or automated infrastructure objects (120b) based on the multitude of data streams and a context model (111a) of the industrial environment, in particular the warehouse. The communication interface (113) is further configured to send the multitude of signals to the multitude of industrial trucks (120a), industrial robots, and/or automated infrastructure objects (120b) in order to control and/or regulate them.