Robot Problem Message Grouping for Faster Fault Diagnosis
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Solution Overview
Problem
Diagnosing the origin of technical problems in multi-robot systems is difficult and time-consuming due to the complexity of problem messages generated by multiple robots, where most messages may not relate to the actual failure, increasing the workload for practitioners.
Innovation Solution
A method that groups problem messages into sets based on time proximity, identifying frequent descriptive data elements within these sets to assign names that can indicate common causes, reducing the amount of data practitioners need to inspect and facilitating the identification of recurring issues through a graphical interface.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If problem messages are collected from multiple robots to facilitate identification of malfunction reasons, then the completeness of problem information is improved, but the complexity of analyzing messages increases and time consumption increases
Solution Approach 1:
The patent segments the large volume of problem messages into smaller groups based on temporal proximity. Messages occurring within a threshold time window are grouped together, creating manageable segments that can be analyzed independently. This segmentation reduces the complexity of analyzing all messages from multiple robots simultaneously while preserving the complete problem information across all segments.
2Measurement precision
If all problem messages are analyzed individually to find the actual failure cause, then the accuracy of problem identification is improved, but the time required for diagnosis increases
Solution Approach 1:
The patent merges problem messages that occur within a predetermined time threshold into unified message sets. By combining related messages temporally, the system maintains accurate problem identification through the collective information in each set while reducing the total number of individual messages that require separate analysis, thus decreasing diagnostic time.
Solution Approach 2:
The patent introduces a temporal parameter (time threshold) to transform the analysis approach. By using time proximity as a criterion for grouping messages, the system changes the parameter of message organization from individual analysis to set-based analysis, thereby reducing diagnostic time while maintaining identification accuracy through the preservation of temporal relationships.
3Quantity of substance
If problem messages from multiple robots are collected to identify failure reasons, then the comprehensiveness of diagnostic data is improved, but the workload for practitioners increases
Solution Approach 1:
The patent segments the comprehensive diagnostic data from multiple robots into temporally-grouped message sets. This segmentation preserves the comprehensiveness of the diagnostic information while organizing it into manageable units that reduce the practitioner's workload by presenting clustered, contextually-related messages rather than a flat list of all individual messages.
4Measurement precision
If individual problem messages are inspected to find recurring issues, then the precision of problem detection is improved, but the efficiency of identifying patterns decreases
Solution Approach 1:
The patent merges problem messages into sets based on temporal proximity, which enables practitioners to efficiently identify recurring issues and patterns within each message set. This merging maintains precise problem detection by preserving the content and context of individual messages while improving pattern identification efficiency through the visual and analytical grouping of related messages that share common causes or characteristics.
Data Source
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AI summary
A method for problem diagnosis in a robot system comprising one or more robots(1a, 1b, 2a, 2b, …) comprises the steps of: a) receiving (S1) a first problem message from a robot of said robot system, the problem message comprising one or more data elements descriptive of a problem experienced by the robot; b) receiving (S1) a subsequent problem message from a robot of said robot system; c) if a time elapsed between receipt of said sub- sequent message and receipt of an immediately pre- ceding message is shorter than a pretedermined threshold (S2), adding said subsequent message to a message set which comprises said immediately pre- ceding message (S3); d) if the time elapsed is longer than the pretedermined threshold (S2), terminating (S4) the message set of the immediately preceding message without adding the subsequent message, and establishing (S5, S6) a new message set in which said subsequent message is the first message; e) in a terminated message set, identifying (S7) at least one descriptive data element which is frequent in the messages of the set or which occurs in a first message of the set; and f)assigning (S8) said at least one descriptive data element as a name to the terminated message set.