Robot Simulation Hierarchy for Reusable Teaching Points
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Solution Overview
Problem
Existing robot simulators face complexity in managing teaching points when operational targets change, requiring reconfiguration of teaching points across different virtual spaces, which is not efficiently addressed by existing technologies.
Innovation Solution
An information processing apparatus that utilizes hierarchical data to manage and output teaching points and models, allowing for the reuse of created elements in different virtual spaces while maintaining relative positions, reducing the need for manual reconfiguration and man-hours.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If teaching points are managed independently from models in conventional robot simulators, then each operational target requires separate teaching point configuration, but this leads to increased device complexity and manual reconfiguration work when layouts change
Solution Approach 1:
The patent merges models and teaching points into a unified hierarchical data structure where teaching points are nested within their associated models. This combination allows teaching points to automatically follow model position changes, eliminating the need for separate management and reducing complexity while improving adaptability to layout changes.
Solution Approach 2:
The patent introduces a hierarchical data structure dimension that organizes teaching points within models within operational targets. This multi-level hierarchy allows teaching points to inherit transformation properties from parent models, enabling automatic adaptation to layout changes without increasing operational complexity.
2Reliability
If teaching points are created for each operational target in robot configuration, then complete coverage of all operational targets is achieved, but this results in loss of time during reconfiguration when layouts change
Solution Approach 1:
The patent establishes hierarchical relationships between models and teaching points in advance, so that when model positions change, associated teaching points automatically update. This preliminary structuring eliminates the need for time-consuming manual reconfiguration while maintaining complete teaching point coverage for all operational targets.
Solution Approach 2:
The hierarchical data structure allows teaching points to be copied along with their parent models when models are moved or replicated. This automatic copying mechanism ensures that teaching point coverage is maintained across layout changes without requiring manual recreation or repositioning.
3Manufacturing precision
If manual reconfiguration of teaching points is performed when operational target layouts change, then teaching points can be updated to match new layouts, but this increases loss of time and reduces productivity
Solution Approach 1:
The patent implements a self-updating system where teaching points automatically adjust their positions based on changes to parent models within the hierarchical structure. This self-service mechanism maintains accurate teaching point positioning without requiring manual intervention, thereby preserving precision while significantly improving productivity.
Data Source
AI summary
An information processing apparatus including a display unit configured to display a state of a robot system based on first data is characterized in that at least one element of the robot system based on the first data can be outputted with second data that is different from the first data.