Robot Task Interruption and Resumption Under Service Schedules
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Solution Overview
Problem
Existing robot operation methods struggle to efficiently manage task interruptions and reordering in dynamic environments, such as changing occupancy levels or unexpected obstacles, while ensuring compliance with service schedules and resource constraints.
Innovation Solution
A method for operating robots that involves providing a service schedule with multiple tasks and parameters, allowing robots to interrupt and resume tasks based on operator input and environmental conditions, and reordering tasks to optimize completion within given parameters.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a robot interrupts a current task to perform an additional task based on operator input, then operational flexibility and adaptability improve, but task completion time and schedule compliance may worsen
Solution Approach 1:
The robot dynamically adjusts its task execution by interrupting current tasks and switching to additional tasks based on real-time operator input and environmental conditions. The system maintains adaptability while managing time loss through dynamic task reordering and priority assignment, allowing the robot to respond flexibly to changing operational requirements without permanently compromising overall task completion
Solution Approach 2:
The system changes task parameters including priority levels, execution timing, and scheduling constraints when interruptions occur. By dynamically modifying these parameters and reordering the task list, the robot balances operational flexibility with time management, ensuring that additional tasks are accommodated while minimizing impact on overall schedule compliance
2Productivity
If a robot reorders tasks to optimize completion within parameters, then productivity improves, but system complexity increases
Solution Approach 1:
The task management system is segmented into distinct functional modules: task reception, parameter evaluation, reordering logic, and execution control. This segmentation allows the complex reordering operation to be broken down into manageable components, improving productivity through systematic task optimization while keeping system complexity organized and maintainable through modular architecture
Solution Approach 2:
The system optimizes productivity by dynamically changing task parameters such as execution order, priority levels, and timing constraints based on current operational context. This parameter-based approach enables flexible task reordering without requiring complex structural changes to the robot's control architecture, thereby improving efficiency while managing complexity through parameter manipulation rather than structural complexity
Data Source
AI summary
A method of operating a robot performing a task when receiving instructions to discontinue the task and perform an additional task. Having performed the additional task, the robot will revert to the position of performing the first task and continue the first task.