Joint-Space Impedance Control for Accurate Robot Manipulators
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Solution Overview
Problem
Current impedance control systems for robot manipulators are prone to position tracking errors due to reliance on end-effector torque/force measurements, which can be impractical and unreliable, and are sensitive to model inaccuracies and external disturbances, especially in applications like surgical robotics.
Innovation Solution
A method for controlling mechanical systems with driven joints that measures torques or forces and implements an impedance control algorithm using mass, damper, and spring terms, allowing for target configuration formation and drive signal generation without relying on end-effector torque/force measurements, and operates in joint space to improve control accuracy and robustness.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If impedance control is implemented using end-effector torque/force measurements, then control accuracy can be improved, but the system becomes unreliable and impractical due to measurement difficulties
Solution Approach 1:
The patent introduces joint torque/force measurements as an intermediary substitute for direct end-effector torque/force measurements. By measuring torques at the joints and using transformation relationships, the system achieves impedance control without requiring difficult-to-obtain end-effector force measurements, thereby maintaining control accuracy while improving reliability
Solution Approach 2:
The patent replaces the mechanical measurement approach at the end-effector with a computational approach using joint space measurements and transformations. Instead of directly measuring end-effector forces, the system uses joint torque measurements combined with kinematic and dynamic models to compute equivalent end-effector forces, substituting a practical mechanical measurement with a computational solution
2Measurement precision
If impedance control relies on accurate robot manipulator models, then control performance can be optimized, but the system becomes sensitive to model inaccuracies
Solution Approach 1:
The patent implements feedback mechanisms that use actual joint torque measurements and position feedback to continuously update and compensate for model inaccuracies. By comparing expected and actual system behavior and adjusting control commands accordingly, the system maintains optimal performance despite imperfections in the robot manipulator model
Solution Approach 2:
The patent employs adaptive parameter adjustment where impedance control parameters are dynamically modified based on real-time measurements and system state. This allows the controller to compensate for model inaccuracies by adjusting parameters such as desired impedance characteristics and transformation matrices to match actual system behavior
3Measurement precision
If traditional impedance control is used, then position tracking can be achieved, but the system is sensitive to external disturbances like friction and obstacles
Solution Approach 1:
The patent converts the harmful effect of external disturbances into useful information by measuring joint torques, which include both commanded and disturbance components. By analyzing these torque measurements and using differential relationships, the system isolates and compensates for disturbance forces, transforming what was previously a source of error into a source of correction information
Solution Approach 2:
The patent uses joint torque measurements as an intermediary that provides information about both commanded forces and external disturbances. This intermediate measurement allows the system to separate and independently handle commanded motion and disturbance compensation, improving robustness against external factors while maintaining position tracking accuracy
Data Source
AI summary
A method for controlling a mechanical system having a plurality of components interlinked by a plurality of driven joints, the method comprising: measuring torques or forces about or at the driven joints and forming a load signal representing the measured torques or forces; receiving a motion demand signal representing a desired state of the system; implementing an impedance control algorithm in dependence on the motion demand signal and the load signal to form a target signal indicating a target configuration for each of the driven joints; measuring the configuration of each of the driven joints and forming a state signal representing the measured configurations; and forming a set of drive signals for the joints by, for each joint, comparing the target configuration of that joint as indicated by the target signal to the measured configuration of that joint as indicated by the state signal.