Human Action Prediction for Anticipatory Robot Collaboration
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Solution Overview
Problem
In manufacturing, tasks requiring human labor such as wire harness assembly and aircraft assembly are tedious and difficult to automate due to dexterity and flexibility requirements, making it challenging for manufacturers to increase production volume and reduce costs.
Innovation Solution
A method and apparatus for human-robot collaboration that acquires visual temporal data from a human partner, predicts future actions using a generative module, and determines the likelihood of future actions through a discriminative module, enabling a robot to plan and perform complementary actions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If tasks requiring human labor are used (e.g., wire harness assembly, aircraft assembly), then dexterity and flexibility requirements are met, but automation difficulty increases and production volume cannot be increased
Solution Approach 1:
The patent merges human workers with robotic systems into a collaborative framework where humans perform tasks requiring dexterity and flexibility while robots handle repetitive and dangerous operations. This combination allows the system to maintain high adaptability for complex tasks while achieving automation benefits for standardized operations, thereby increasing production volume without sacrificing dexterity requirements.
Solution Approach 2:
The collaborative framework creates a multi-functional system where human workers can adapt to various complex tasks requiring judgment and dexterity, while robotic systems provide universal automation capabilities for repetitive operations. This multi-functionality allows the same system to handle both highly adaptive tasks and highly automated tasks, resolving the contradiction between adaptability and automation extent.
2Adaptability or versatility
If human labor is used for tasks, then dexterity and flexibility are maintained, but production volume increases become challenging
Solution Approach 1:
By merging human workers with robotic systems in a collaborative framework, the system leverages human adaptability for complex tasks while utilizing robotic capacity for high-volume repetitive operations. This combination enables the system to maintain dexterity and flexibility requirements while simultaneously achieving significant increases in production volume that would be difficult to accomplish with purely manual labor.
3Adaptability or versatility
If human labor is used for tasks, then flexibility requirements are met, but labor costs increase
Solution Approach 1:
The collaborative framework merges human workers with robotic systems to create a cost-effective solution where humans perform tasks requiring flexibility and judgment, while robots handle repetitive operations that would otherwise require large numbers of human workers. This division of labor maintains the necessary flexibility requirements while reducing overall labor costs through automation of suitable tasks.
Data Source
AI summary
A method for human-robot collaboration including: acquiring visual temporal data of a human partner to a robot; determining, using a generative module, predicted future visual temporal data in response to the visual temporal data, the visual temporal data including current visual temporal data and previous visual temporal data; and determining, using a discriminative module, a vector of probabilities indicating the likelihood that a future action of the human partner belongs to each class among a set of classes being considered in response to at least the future visual temporal data and the visual temporal data.