Robot Task Resumption Control for Mid-Process Failure Recovery
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Solution Overview
Problem
Existing systems for resuming robot operations after a failure require users to return the robot to an initial state and restart from the first work, leading to inefficiencies and increased complexity, especially when resuming from a mid-process state.
Innovation Solution
A task resumption system that includes processing circuitry to receive a task resumption specification, acquire the current and resume states of a device, and transition the device to the resume state, allowing it to resume the task from the specified point.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the robot returns to the initial state and restarts from the first work after a failure, then the system ensures complete state restoration, but the productivity decreases due to re-executing unnecessary tasks
Solution Approach 1:
The protocol chart is divided into multiple work segments, each representing a discrete task. When a failure occurs, the system identifies the specific work segment where the failure happened and resumes from that segment rather than restarting the entire protocol. This segmentation allows selective re-execution of only the necessary portion of the workflow.
Solution Approach 2:
The system performs preliminary identification of the failure point and calculates the resume state before actually resuming execution. By determining in advance which work segment needs to be restarted and what the appropriate resume state should be, the system avoids unnecessary re-execution of completed tasks while ensuring reliable state restoration.
2Device complexity
If the robot restarts from the first work after a failure, then the system simplifies the resumption logic, but the loss of time increases due to re-executing completed tasks
Solution Approach 1:
The system replaces manual tracking of work progress with an automated information processing mechanism. The control device automatically identifies the failure point, determines the resume state, and calculates which work segment should be restarted. This information-based approach eliminates the need for complex manual state tracking while enabling fast resumption.
Solution Approach 2:
The system introduces an intermediary information processing layer that sits between the failure detection and the resumption execution. This intermediary component automatically determines the resume state and generates the appropriate resume command, simplifying the overall resumption logic while reducing time loss through automated decision-making.
3Productivity
If the system allows resumption from any work segment, then the productivity improves by avoiding re-execution of completed tasks, but the device complexity increases due to state tracking requirements
Solution Approach 1:
The control device performs multiple functions: it monitors execution progress, identifies failure points, determines resume states, and generates resume commands. By consolidating these functions into a single control device that can handle all aspects of protocol management, the system achieves high productivity without proportionally increasing overall system complexity.
Solution Approach 2:
The system creates and manages information copies of the protocol chart and execution state. By working with information representations rather than physical state changes, the system can track progress and determine resume states efficiently. The information-based approach allows complex state tracking without requiring complex physical mechanisms.
4Reliability
If the robot resumes from the first work after a failure, then the system ensures complete task execution, but the quantity of executed tasks increases due to re-executing unnecessary works
Solution Approach 1:
The resumption point is made dynamic rather than fixed. Instead of always restarting from the first work, the system dynamically determines the appropriate resume state based on where the failure occurred. This dynamic approach ensures that only the necessary number of tasks are re-executed, reducing the total quantity of executed tasks while maintaining execution completeness.
Solution Approach 2:
The system uses feedback from the failure detection to adjust the resumption strategy. By monitoring which work segment failed and using this information to determine the appropriate resume state, the system avoids re-executing tasks that were already successfully completed. This feedback mechanism ensures task execution completeness while minimizing the quantity of repeated tasks.
Data Source
AI summary
A task resumption system including processing circuitry that receives a task resumption specification for task resumption by a device when the device, which sequentially performs multiple tasks, stops during processing, acquires a current state of the device, acquires a resume state corresponding to the task resumption of the device, causes the device to transition from the current state to the resume state, and causes the device to resume the task according to the resume state.