Robot Exception Routing for Assisted Retail Task Completion
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Solution Overview
Problem
Robotic units operating in retail environments face challenges in completing tasks due to exceptions such as product identification, location, and computational issues, which existing systems are not adequately equipped to handle autonomously.
Innovation Solution
A system and method that classify exception signals generated by robotic units to determine the appropriate level of assistance needed, directing intervention requests to a network of centers staffed and equipped to provide support, including data assistance, first response, and second response centers for product identification, navigation, and programming assistance respectively.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If robotic units operate autonomously in retail environments, then productivity is improved, but reliability deteriorates due to inability to handle exceptions
Solution Approach 1:
The patent introduces a human assistance network as an intermediary between the robotic unit and complex exceptions. When the robotic unit encounters an unhandled exception type, it requests human assistance through a communication interface. This mediator approach allows the robot to maintain high autonomy for routine tasks while reliably handling edge cases through human intervention, thus resolving the contradiction between productivity and reliability.
2Reliability
If robotic units handle all exception types autonomously, then reliability is improved, but device complexity increases
Solution Approach 1:
The patent segments exception handling into two distinct levels: autonomous handling for recognized exception types and human-assisted handling for unrecognizable types. The robotic unit's control system is divided into an exception detection module that identifies exception types and a communication interface that requests human assistance when needed. This segmentation allows the system to maintain reliability without requiring the full complexity of handling every possible exception autonomously.
3Reliability
If robotic units request human assistance for all exceptions, then reliability is improved, but loss of time increases
Solution Approach 1:
The patent applies partial action by having the robotic unit autonomously handle only those exception types it is trained to recognize, while requesting human assistance only for unrecognizable types. This selective approach ensures that common, routine exceptions are resolved quickly without human intervention, minimizing time loss, while still maintaining high reliability through human assistance for edge cases that the robot cannot handle alone.
Data Source
AI summary
A robotic unit for manipulating items and products may receive assistance from a product management system if an exception occurs indicating the robotic unit cannot complete a given task with respect to handling the product. The product management system may be associated with a plurality of different assistance centers and response centers providing different types or levels of assistance. The product management system can classify the exception according to hierarchal tiers to determine the type of assistance required. The product management system can then generate and direct an intervention request to one of the response centers based on the classification. The assistance and response centers may be equipped and staffed to provide particularized assistance to the robotic unit. In an example, the robotic unit may store data and instructions received from the assistance and response center for future implementation.