Adaptive Robot Tele-Operation Using Role-Based Control Paradigms
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Solution Overview
Problem
Existing robot control systems lack the ability to adapt and improve over time based on operator feedback and task-specific paradigms, leading to inefficient operation and decision-making.
Innovation Solution
A robot system that selects and updates control paradigms based on operator identity, role, or task, using feedback mechanisms to enhance decision-making and adapt over time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a robot uses a fixed control paradigm, then the system complexity is reduced, but the adaptability to different operators and tasks deteriorates
Solution Approach 1:
The control system dynamically selects and switches between multiple control paradigms based on operator identity, task type, and performance metrics. The system transitions from a static fixed paradigm to a dynamic adaptive paradigm that evolves with feedback, resolving the contradiction between simplicity and adaptability.
Solution Approach 2:
The system changes control parameters by selecting different control paradigms (e.g., autonomous, semi-autonomous, tele-operated modes) based on operational context. This allows the robot to adapt its control characteristics without increasing fundamental system complexity.
2Adaptability or versatility
If a robot implements multiple control paradigms, then the adaptability improves, but the device complexity increases
Solution Approach 1:
The control system is designed with multi-functionality to handle multiple control paradigms within a single unified architecture. The processing unit can execute different control strategies (autonomous navigation, semi-autonomous collaboration, full tele-operation) using the same hardware platform, avoiding the need for separate systems for each paradigm.
Solution Approach 2:
The system uses feedback mechanisms to automatically select and switch between control paradigms based on operator performance, task requirements, and environmental conditions. This feedback-driven selection reduces the perceived complexity by automating the decision-making process rather than requiring manual configuration.
3Ease of operation
If the robot operates with basic control capabilities, then the ease of operation is maintained, but the productivity deteriorates
Solution Approach 1:
The control system is segmented into multiple operational modes with increasing levels of autonomy and capability. Operators can select from basic tele-operated mode for simple tasks to advanced autonomous mode for complex tasks, allowing ease of operation to be maintained for simple operations while enabling high productivity when needed.
Solution Approach 2:
The robot dynamically adjusts its operational capabilities based on the selected control paradigm and task requirements. The system can transition between basic and advanced functionalities, ensuring that operators experience ease of operation for routine tasks while the system delivers high productivity for demanding tasks.
Data Source
AI summary
The present disclosure describes robots and tele-operation systems where a select control paradigm is selected from a plurality of control paradigms based on an identity of an operator, role of an operator, or expected tasks to be performed by the robot. Generic robots can be operated in accordance with any of the plurality of control paradigms, such that any of said generic robots can serve a role or act as an assistant to an operator by selection of an appropriate control paradigm. Control paradigms can be operator specific, or specific to a faction or role which an operator fits in, or specific to a set of tasks to be performed by the robot. The present disclosure also describes feedback mechanisms by which a robot or tele-operator system receive operator feedback and update a control paradigm, to gradually improve the control paradigm over time.