Wearable Robot Admittance Control for Inertial Resistance
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Solution Overview
Problem
Existing wearable robots experience significant resistance reactions due to their inertia, making it difficult to accurately reflect the user's intention and resulting in unnatural and fatiguing movements.
Innovation Solution
A method and system that determine human torque applied to the robot, calculate target angular velocity using an admittance model, and apply an optimal control gain to minimize resistance by operating the robot's joints with both user-applied torque and required torque, effectively reducing the resistance felt by the user.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If the robot is driven by calculating joint torque from user-applied force, then the robot can operate the joint, but significant resistance reaction is caused by the robot's inertia
Solution Approach 1:
The control system performs preliminary calculation of required torque by considering the difference between target angular velocity (derived from user torque via admittance model) and actual angular velocity. This preliminary action allows the system to preemptively compensate for inertial resistance, thereby reducing the resistance reaction felt by the user during robot operation.
Solution Approach 2:
The control system continuously measures the actual angular velocity of the robot joint and feeds it back to the control unit. This feedback is used to calculate the velocity difference from the target angular velocity, which then informs the required torque calculation. This closed-loop feedback mechanism enables real-time adjustment to minimize resistance reaction while maintaining ease of operation.
2Productivity
If the robot uses simple force-to-torque conversion, then the control scheme is simple, but the robot cannot promptly react to user's initial intention to move
Solution Approach 1:
The admittance model serves as an intermediary between the user-applied torque and the target angular velocity. Instead of directly converting force to torque for joint operation, the system uses the admittance model to transform user torque into a desired velocity profile. This intermediary transformation enables the robot to promptly react to the user's initial movement intention while maintaining a manageable control architecture.
Solution Approach 2:
The control system transforms the control parameter from direct torque control to velocity control via the admittance model. By changing the parameter representation (from torque directly to angular velocity through an intermediate transformation), the system achieves faster reaction to user intention. The optimal control gain further refines this parameter transformation to balance responsiveness with control smoothness.
3Stability of the object's composition
If the robot operates with high inertia, then the robot structure is stable, but the resistance reaction increases and user fatigue increases during prolonged use
Solution Approach 1:
The control system replaces pure mechanical torque application with a智能化 control approach that calculates required torque based on velocity differences. Instead of relying solely on mechanical inertia for stability, the system uses control algorithms (admittance model + optimal control gain) to achieve stability while minimizing resistance. This substitution of mechanical direct control with intelligent control reduces the harmful resistance reaction while maintaining structural stability.
Data Source
AI summary
A system for controlling driving of a wearable robot may include a drive unit for operating a drive joint of the robot, a measurement unit for measuring an actual angle and an actual angular velocity of the drive joint in the robot, a sensing unit for determining a human torque applied by a wearing user to the drive joint, and a control unit for determining a target angular velocity of the robot by applying the determined human torque to an admittance model and for determining a required torque that may be input to the drive unit of the robot by applying an optimal control gain to a difference between the target angular velocity and the actual angular velocity of the robot.