Model-less Control for Continuum Manipulator Position and Force
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Solution Overview
Problem
Traditional robotic control techniques for continuum manipulators face challenges in modeling irregular configurations and unknown environmental constraints, leading to instabilities and workspace limitations, as they rely on precise calibration and accurate kinematic and mechanical models.
Innovation Solution
A model-less control system for continuum manipulators that incorporates position/force control, using sensors to detect position and force information, and a controller that updates a control matrix to provide adaptive control commands, allowing the manipulator to operate in constrained and unknown environments without relying on precise modeling.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If model-based control techniques are used for continuum manipulators, then control precision can be improved through accurate modeling, but the system becomes unable to adapt to unknown environmental constraints and irregular configurations
Solution Approach 1:
The control system performs self-calibration by automatically updating its control matrix based on sensor feedback from the actual manipulator configuration. Instead of relying on pre-established models, the system serves itself by learning the actual kinematic relationships through operation, eliminating the need for manual modeling and calibration.
Solution Approach 2:
The system continuously receives feedback from sensors measuring manipulator configuration and environmental constraints, then uses this feedback to update the control matrix in real-time. This closed-loop feedback mechanism enables the system to adapt to unknown environments and maintain control precision without requiring accurate prior models.
2Manufacturing precision
If precise calibration between model and manipulator is performed, then control accuracy is improved, but the system becomes sensitive to environmental uncertainties and configuration changes
Solution Approach 1:
The control matrix is transformed from a static, pre-calibrated parameter set into a dynamic structure that continuously adapts to changing manipulator configurations and environmental constraints. The system recalibrates itself in real-time based on actual operating conditions, maintaining reliability across varying environments.
Solution Approach 2:
The system changes the control parameters (control matrix elements) dynamically based on sensor feedback rather than maintaining fixed calibrated values. This allows the control parameters to adapt to environmental uncertainties and configuration changes, preventing the sensitivity problems associated with rigid precise calibration.
3Area of stationary object
If model-based control is used to account for environmental constraints, then workspace coverage can be improved, but the system experiences instabilities and workspace limitations due to modeling errors
Solution Approach 1:
The system replaces the mechanical modeling approach with a sensor-based feedback approach. Instead of using a mathematical model to predict manipulator behavior under environmental constraints, the system directly measures the actual configuration and uses sensor feedback to update control commands, eliminating modeling errors and their associated instabilities.
Data Source
AI summary
A method includes receiving position information and force information, providing control commands to a steering mechanism of a continuum manipulator based on the position information and the force information, updating a control matrix based on the position information and the provided control commands, and providing updated control commands to the steering mechanism based on the updated control matrix. A continuum manipulator includes a body, a steering mechanism configured to steer the body, sensors, and a controller. The sensors include a position sensor to detect a position of the body and a force sensor to detect a force against the body. The controller is configured to receive position information from the position sensor and force information from the force sensor, provide control commands to the steering mechanism based on the position information and the force information, and update a control matrix based on the position information and the provided control commands.