Robotic Floor Map Generation for Logistics Layout Iteration
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Solution Overview
Problem
Manual design of large-scale logistics facilities is time-consuming, labor-intensive, and prone to errors due to the complexity of variable spaces, leading to inefficient resource utilization and throughput optimization.
Innovation Solution
A system and method for generating candidate maps from a baseline map using input parameters to optimize storage and travel lane placement, involving a map generator and qualification system that simulates operations to select qualified maps that satisfy performance objectives.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual design methods are used for large-scale logistics facilities, then design flexibility and human judgment are maintained, but the design process becomes time-consuming and error-prone
Solution Approach 1:
The patent uses baseline maps as templates that can be copied and modified to generate candidate maps. Instead of creating designs from scratch, the system replicates proven layouts and adapts them to new requirements, dramatically reducing design time while maintaining reliability through proven patterns
Solution Approach 2:
The system performs preliminary actions by pre-defining baseline maps with optimal characteristics and pre-establishing qualification criteria. This allows the design process to start from validated templates rather than requiring all decisions to be made during the design process itself
2Productivity
If manual design is used, then human expertise can be applied, but the ability to analyze variable space and iterate designs is limited
Solution Approach 1:
The patent implements a dynamic design system where baseline maps can be modified through various transformations to generate multiple candidate maps. The system dynamically adapts designs by applying transformations such as scaling, rotating, and modifying specific features of baseline maps to explore the variable space of possible designs
Solution Approach 2:
The design system segments the complex task of logistics facility design into manageable components: baseline map selection, transformation application, candidate map generation, and qualification testing. This segmentation allows each component to be optimized independently while maintaining overall system productivity
3Productivity
If automated map generation is implemented, then design speed and resource optimization improve, but system complexity increases
Solution Approach 1:
The patent implements feedback loops where candidate maps are automatically qualified against predefined criteria, and results feed back into the generation process. The qualification system evaluates each candidate map and provides feedback that guides subsequent map generation, creating a self-correcting automated system that improves with each iteration
Solution Approach 2:
The system uses universal baseline maps that can serve multiple purposes and be adapted to different scenarios. A single baseline map can be transformed into multiple candidate maps for different facility types and requirements, reducing the need for numerous specialized design templates while maintaining high productivity
Data Source
AI summary
A system can be configured to generate and analyze one or more candidate logistics maps based on a set of input parameters and a baseline map of a logistics facility. The system can identify modifications strategies, resource limits, regions of interest, mapping constraints through analysis of the input parameters and the baseline map. The generated candidate maps and the baseline map can be implemented in virtual environments that are configured to replicate one or more operations associated with the baseline map, such as item distribution, item retrieval, and reorganization operations. The virtual environment can further simulate the resource limits associated with the baseline map and compare performance indicators from simulation of the baseline map to performance indicators from simulation of the candidate maps to identify viable improvements over existing logistics solutions.