Robot Joint Impedance Control Without End-Effector Force Sensors
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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 where multiple joint configurations and singular poses complicate inverse kinematics solutions.
Innovation Solution
A method for controlling mechanical systems with driven joints that involves receiving motion demand signals, measuring joint configurations and torques, implementing an impedance control algorithm using ordinary differential equations with impedance parameters derived from joint state signals, and performing inverse kinematic computations to determine suitable joint configurations, thereby forming drive signals to achieve target positions without relying on end-effector torque/force measurements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If impedance control is implemented using end-effector torque/force measurements, then impedance control functionality is achieved, but position tracking accuracy deteriorates due to measurement errors and model inaccuracies
Solution Approach 1:
The patent introduces an intermediary approach by using joint torque measurements instead of end-effector torque measurements. The joint torques serve as intermediate variables that can be accurately measured at the joint level and then transformed to compute end-effector forces, thereby avoiding the direct measurement problems at the end-effector while maintaining impedance control functionality
Solution Approach 2:
The patent replaces the mechanical measurement approach at the end-effector with a computational approach using joint-level measurements and inverse kinematics/dynamics calculations. This substitution transforms the problem from direct physical measurement to mathematical computation, improving accuracy by avoiding measurement errors
2Reliability
If end-effector torque/force sensors are used for impedance control, then impedance regulation is achieved, but system cost and complexity increase
Solution Approach 1:
The patent makes the existing joint torque sensors serve multiple functions: they are used for both position control and impedance control. By utilizing the same sensors for multiple purposes through computational transformation, the system achieves impedance regulation without requiring additional end-effector sensors
Solution Approach 2:
The system uses its own existing joint torque measurements and computational models to achieve impedance control functionality that would otherwise require separate end-effector sensors. The robot's existing sensing and computation capabilities serve the impedance control function
3Manufacturing precision
If inverse kinematics is tightly coupled with position control loop, then position control is achieved, but computational burden and sensitivity to model errors increase
Solution Approach 1:
The patent segments the control architecture by separating inverse kinematics computations from the inner position control loop. The control is divided into an inner loop for position control and an outer loop for impedance control, with each handling specific computational tasks to reduce overall complexity
Data Source
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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 the 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.