Human-AI Remote Robot Control for Adaptive Cyber Manufacturing
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Solution Overview
Problem
Existing robotic systems in manufacturing environments face challenges in enabling workers to perform a variety of tasks remotely, particularly in complex environments, and there are concerns regarding human trust, cybersecurity, and inclusivity, which affect worker satisfaction, safety, and team performance.
Innovation Solution
An adaptive cyber manufacturing system that dynamically adjusts its behavior based on user performance, incorporating machine learning to sense user conditions and emotions, allowing for real-time operational mode changes to enhance trust and safety, and providing an inclusive platform for diverse workers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If robotic systems are used to perform manufacturing tasks without human intervention, then productivity is improved, but the ability to handle complex tasks requiring human judgment and interaction deteriorates
Solution Approach 1:
The patent merges robotic automation with human oversight by implementing a collaborative framework where robots handle routine tasks while human workers monitor and intervene in complex situations. This combination allows the system to maintain high productivity through automation while preserving adaptability for complex tasks requiring human judgment.
Solution Approach 2:
The system dynamically adjusts the level of automation based on task complexity and real-time conditions. For routine, high-volume tasks, the system operates autonomously to maximize productivity. For complex or unpredictable tasks, the system transitions to human-controlled or human-supervised modes, enabling versatile handling of diverse manufacturing challenges.
2Extent of automation
If advanced AI technologies are integrated into manufacturing systems, then automation capability is improved, but human trust and acceptance deteriorate due to cybersecurity concerns and lack of transparency
Solution Approach 1:
The patent implements feedback mechanisms that provide transparent information about AI decision-making processes to human workers. The system monitors AI performance, detects anomalies, and communicates system status and reasoning to users, building trust through visibility and accountability while maintaining high automation levels.
Solution Approach 2:
The system introduces human workers as intermediaries between fully autonomous AI systems and physical manufacturing operations. This hybrid approach allows advanced AI capabilities to be deployed while human oversight maintains trust and acceptance, creating a collaborative layer that bridges automation and human judgment.
3Object-affected harmful factors
If remote controlled robotic devices are deployed, then worker safety is improved, but worker satisfaction and collaboration deteriorate due to reduced human interaction
Solution Approach 1:
The patent implements partial remote control where workers can operate robots remotely when safety is critical, but switch to local operation or collaborative modes when interaction and satisfaction are priorities. This selective approach provides safety benefits for dangerous tasks while preserving social benefits for routine operations.
Solution Approach 2:
The robotic system is designed with multi-functionality, capable of operating in fully autonomous mode, remote-controlled mode, and collaborative mode. This universality allows the same system to adapt to different task requirements and social preferences, providing safety when needed while maintaining worker satisfaction through appropriate levels of human interaction.
Data Source
AI summary
An adaptive cyber manufacturing facility method and system is disclosed for performing a task remotely on an object at an adaptive cyber manufacturing facility having a robotic device. The method may include receiving, via a computing device, cyber manufacturing system data; reporting the cyber manufacturing system data to a remote user of the robotic device via a user interface; acquiring user condition data regarding a condition of the user via the computing device; acquiring instructions from the user interface for remotely operating the robotic device to perform the task; automatically selecting a cyber manufacturing system operational mode from a plurality of pre-defined cyber manufacturing system operational modes based on the user condition data; and causing control of the robotic device to perform the task on the object according to the instructions from the user interface based on rules associated with the selected cyber manufacturing system operational mode.