Robotic Workspace Layout Planning With Representative Candidate Search
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Automated manufacturing processes face inefficiencies due to suboptimal workspace layouts, which can impact production efficiency and cost, as existing methods require evaluating all possible layouts, leading to computational expense and often necessitate human supervision.
Innovation Solution
A computer-implemented method for planning workspace layouts that generates optimal configurations by evaluating a representative subset of candidate layouts using objective functions, optimizing resource selection and robot placement, and iteratively refining layouts to balance performance and cost criteria.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If all possible workspace layouts are evaluated to determine the optimal layout, then the layout optimization accuracy is improved, but the computational expense and time consumption increase significantly
Solution Approach 1:
The patent segments the workspace into discrete regions and evaluates layouts hierarchically, first determining optimal regions and then optimal positions within those regions. This segmentation allows the system to evaluate a representative subset of layouts rather than all possible layouts, significantly reducing computational time while maintaining optimization accuracy.
Solution Approach 2:
The patent evaluates only a representative subset of candidate layouts rather than all possible layouts. By using heuristics to generate and evaluate only the most promising layouts, the system achieves sufficient optimization accuracy without the excessive computational burden of exhaustive evaluation.
2Manufacturing precision
If a comprehensive evaluation of all candidate layouts is performed, then the quality of workspace layout optimization is improved, but the device complexity and computational resources required increase
Solution Approach 1:
The evaluation process is segmented into multiple stages: generating candidate layouts, evaluating layouts against criteria, and selecting optimal layouts. This segmentation allows the system to manage complexity by processing layouts in stages rather than evaluating all layouts simultaneously, reducing the burden on computational resources.
Solution Approach 2:
The system performs partial evaluation by assessing only the most critical aspects of each layout (such as robot reachability, collision avoidance, and task completion time) rather than conducting a comprehensive analysis of every possible parameter. This partial evaluation maintains optimization quality while reducing computational complexity.
3Productivity
If the workspace layout is optimized considering multiple criteria (cost, performance, etc.), then the overall fabrication process efficiency is improved, but the complexity of the optimization process increases
Solution Approach 1:
The patent implements a universal optimization framework that can evaluate multiple criteria (cost, performance, time, resource utilization) simultaneously through a single integrated system. This multi-functional approach allows the system to consider various factors in layout optimization without requiring separate optimization processes for each criterion, thereby managing complexity while improving overall fabrication efficiency.
Solution Approach 2:
The system uses feedback from layout evaluations to iteratively improve the optimization process. By analyzing the results of each layout evaluation against multiple criteria, the system adjusts its search strategy and focuses subsequent evaluations on the most promising candidates, reducing the complexity of multi-criteria optimization through adaptive learning.
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.