Joint-Space Impedance Control for Accurate Robot Manipulation
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Solution Overview
Problem
Current impedance control systems for robot manipulators are prone to position tracking errors due to reliance on inaccurate models, sensitivity to external disturbances, and the impracticality of measuring contact torque/force at the end effector, 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 determination and drive signal formation without relying on end-effector force measurement, and operates in joint space to reduce computational complexity and improve accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If impedance control is implemented using end-effector force measurement, then control accuracy can be improved, but device complexity and cost increase due to additional sensors
Solution Approach 1:
The patent uses joint torque measurements as an intermediary to infer end-effector contact forces. Instead of directly measuring end-effector forces with complex force sensors, the system measures joint torques (which are easier to obtain from motor current) and uses the robot's dynamic model and kinematics to calculate the corresponding end-effector forces. This intermediary approach achieves the same control objective with simpler, less expensive sensors.
Solution Approach 2:
The patent replaces direct mechanical force measurement at the end-effector with an indirect calculation based on joint torque measurements and dynamic modeling. By substituting the need for complex mechanical force sensors with a computational approach using readily available joint torque data, the system reduces hardware complexity while maintaining control accuracy.
2Reliability
If inverse dynamics modeling is used for impedance control, then theoretical control performance can be improved, but reliability decreases due to sensitivity to model inaccuracies
Solution Approach 1:
The patent incorporates feedback from actual joint torque measurements and position sensors to continuously update and correct the control signals. This feedback mechanism compensates for model inaccuracies by using real-time measured data rather than relying solely on theoretical model predictions, thereby improving reliability despite imperfect modeling.
Solution Approach 2:
The patent adjusts impedance parameters (mass, damping, stiffness) based on the specific application requirements and robot configuration. By optimizing these parameters empirically rather than relying purely on theoretical calculations, the system adapts to real-world conditions and compensates for model inaccuracies, improving actual control performance.
3Measurement precision
If impedance control is implemented in Cartesian space, then end-effector control can be improved, but computational complexity increases due to inverse dynamics requirements
Solution Approach 1:
The patent segments the control problem into independent joint-space calculations rather than solving a single complex Cartesian-space inverse dynamics problem. By working in joint space, each joint's contribution to the overall impedance control can be calculated separately and then combined, significantly reducing computational complexity while maintaining end-effector control precision.
Solution Approach 2:
The patent inverts the traditional approach by working forward from joint space to task space rather than computing backward from task space to joint space. Instead of using inverse dynamics to map desired end-effector accelerations to joint torques, the system computes joint accelerations from measured joint torques and then transforms to end-effector space, avoiding the computationally intensive inverse dynamics calculation.
4Device complexity
If conventional position control is used, then system simplicity can be maintained, but adaptability decreases when external disturbances or obstructions are present
Solution Approach 1:
The patent implements dynamic impedance control that allows the robot to adapt its mechanical impedance (stiffness, damping, mass characteristics) in real-time based on interaction forces. This dynamic adjustment enables the system to maintain simplicity in the control architecture while gaining adaptability to external disturbances, obstructions, and varying task requirements by modulating impedance parameters during operation.
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.