Robot Cooperation Control in Shared Human Workspaces
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Solution Overview
Problem
Current robotic systems lack effective methods for cooperative behavior planning, especially in shared workspaces with human operators, as existing approaches are tailored to specific scenarios and do not provide a general solution for optimizing joint actions towards common goals.
Innovation Solution
A method that quantifies cooperative behavior using a partial information decomposition framework to optimize joint actions between autonomous devices and human operators, enabling maximally cooperative behavior by determining synergistic contributions and adapting actions to achieve shared goals efficiently.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If robotic systems operate in isolated workspaces with strict separation from human operators, then safety and control are maintained, but collaboration and task efficiency are limited
Solution Approach 1:
The patent merges previously separate robotic and human workspaces into a shared collaborative workspace, enabling direct interaction and cooperation between robotic systems and human operators to perform shared tasks more efficiently
Solution Approach 2:
The control system is designed to handle multiple operation modes including isolated robotic operation, human-only operation, and collaborative operation, making the system universally adaptable to different task requirements and safety levels
2Productivity
If collaborative robotic systems share workspace with humans and enable direct interaction, then task efficiency and flexibility improve, but behavior planning complexity increases
Solution Approach 1:
The behavior planning is segmented into distinct operational modes (isolated operation, collaborative operation, human-only operation), allowing the control system to select appropriate planning strategies for each mode and reducing overall complexity
Solution Approach 2:
The system dynamically adapts its behavior planning approach based on the current operational mode and task requirements, transitioning between different planning strategies as needed rather than using a single complex planning system
3Reliability
If robotic systems are designed for specific collaborative scenarios, then performance in those scenarios improves, but adaptability to other scenarios decreases
Solution Approach 1:
The control system is designed with universal behavior planning capabilities that can handle multiple operational modes and task types, making the robotic system adaptable to various collaborative scenarios without requiring scenario-specific redesign
Data Source
AI summary
A method for controlling at least one autonomous device which is one of at least two agents that cooperatively perform a common task in a common environment is provided. The method comprises: obtaining variables on a current state of each agent in the common environment, and obtaining a further variable on a current state of the common environment that describes a distance of the current state of the agents to a common goal state or a task success; determining a quantitative measure for cooperative behaviour of the agents that quantifies an extent to which a mutual support or an adaption in joint cooperative actions towards the common goal state increases a joint action space of the agents; optimizing a joint behaviour of the agents using the quantitative measure based on the obtained variables to determine an action of the autonomous device; and outputting a control signal for controlling the action.