Robot Task Group Scheduling for Synchronized Completion Times
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Solution Overview
Problem
Existing robot control methods struggle to synchronize the completion times of multiple tasks, leading to variations in task completion timing when optimizing for minimal cycle time.
Innovation Solution
A control device and method that classify tasks into groups and generate operation sequences to synchronize the completion times of tasks within each group, using task group generation and operation sequence generation units to optimize task timing and minimize variations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the operation sequence is optimized to minimize cycle time, then productivity is improved, but the completion time variation of tasks increases
Solution Approach 1:
The patent segments tasks into multiple groups based on their completion time characteristics. By dividing the task set into distinct groups (first task group, second task group, etc.), the system can apply different scheduling strategies to each group, thereby controlling completion time variation within groups while maintaining overall productivity.
Solution Approach 2:
The patent dynamically adjusts the operation sequence by selectively executing tasks from different groups based on real-time conditions. The control device determines whether to execute tasks from the first group or second group based on completion time comparisons, creating a dynamic scheduling approach that balances cycle time optimization with completion time synchronization.
2Productivity
If tasks are executed to minimize overall completion time, then productivity increases, but task synchronization deteriorates
Solution Approach 1:
Tasks are segmented into multiple groups with different scheduling priorities. The first task group contains tasks optimized for minimal completion time, while the second task group contains tasks optimized for synchronization. This segmentation allows the system to maintain both productivity and synchronization by selecting appropriate groups based on current needs.
Solution Approach 2:
The system changes the scheduling parameter (which task group to execute) based on the comparison of completion times. When the difference between completion times of tasks in different groups exceeds a threshold, the system switches between groups to maintain synchronization, thereby adjusting operational parameters dynamically.
3Adaptability or versatility
If the robot executes multiple tasks with different priorities, then adaptability improves, but control complexity increases
Solution Approach 1:
The control system manages complexity by segmenting tasks into predefined groups with distinct characteristics. Rather than handling all tasks individually with complex priority arbitration, the system simplifies control by managing two groups with clear execution rules, thereby maintaining adaptability while reducing control complexity.
Solution Approach 2:
The system uses parameter-based decision making (comparing completion time differences against thresholds) to simplify control logic. By changing operational parameters (which group to execute) based on simple comparisons rather than complex multi-criteria optimization, the system maintains adaptability with reduced control complexity.
Data Source
AI summary
A control device 1A includes a task group generation means 16A and an operation sequence generation means 17A. The task group generation means is configured to generate, in a case where multiple tasks to be executed by one or more robots are designated, one or more task groups obtained by classifying the multiple tasks. The operation sequence generation means 17A is configured to generate one or more operation sequences of the one or more robots for completing the multiple tasks so as to put completion time of tasks included in the one or more task groups close to one another.