Robotic Workspace Layout Planning Under Search Time Constraints
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Solution Overview
Problem
Current manufacturing processes face inefficiencies in optimizing workspace layouts for automated fabrication processes, as existing methods require evaluating all possible layouts, which is computationally expensive and time-consuming, and often require significant human supervision.
Innovation Solution
The system automatically generates an optimized workspace layout by selecting robots and their locations using a computer-implemented method that evaluates a representative subset of candidate layouts based on objective functions, such as cost and performance criteria, and iteratively refines the layout using techniques like gradient descent or decision trees.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If all possible workspace layouts are evaluated to determine the optimal layout, then the optimization accuracy is improved, but the computational time and resources increase significantly
Solution Approach 1:
The patent segments the workspace into discrete zones and evaluates layouts incrementally by dividing the search space into manageable sections, allowing optimization without exhaustive evaluation of all possible configurations
Solution Approach 2:
The system performs preliminary evaluation of layout candidates using heuristic rules and constraints before detailed optimization, pre-filtering promising configurations to reduce the computational burden of full evaluation
2Measurement precision
If all possible workspace layouts are evaluated to determine the optimal layout, then the optimization accuracy is improved, but the computational resources increase significantly
Solution Approach 1:
The patent applies partial action by evaluating only a representative subset of layout candidates rather than all possible layouts, using statistical sampling and heuristic selection to achieve satisfactory optimization with reduced computational resource requirements
Solution Approach 2:
The system changes evaluation parameters dynamically, adjusting the threshold for layout acceptance and the depth of optimization based on computational resource availability, allowing flexible trade-off between accuracy and resource consumption
3Productivity
If automated layout planning is implemented, then productivity is improved, but the system complexity increases
Solution Approach 1:
The automated layout planning system performs self-configuration by automatically generating and evaluating layout candidates without requiring manual intervention, thereby improving productivity while managing system complexity through autonomous operation
Solution Approach 2:
The system incorporates feedback loops where layout evaluation results inform subsequent optimization iterations, allowing the system to learn from previous evaluations and improve automatically, reducing the need for complex manual tuning
Data Source
AI summary
This specification describes systems, methods, devices, and other techniques for planning workspaces for automated fabrication processes. A computing system facilitates planning by receiving a set of parameters for planning a layout of a workspace for an automated fabrication process, and generating a plurality of candidate workspace layouts, including selecting, for each candidate workspace layout, (i) one or more robots for performing tasks in the automated fabrication process and (ii) corresponding locations for the one or more robots within the workspace. The system determines an optimal workspace layout based on the plurality of candidate workspace layouts, generates a workspace layout specification for the optimal workspace layout, and provides the workspace layout specification to one or more second computing systems.