Humanoid Robot Balance Control Using Feedforward Joint Compensation
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Solution Overview
Problem
Traditional static balance control methods for humanoid robots rely on feedback control, which responds after deviations occur, leading to lag and inability to prevent interference, compromising stability and balance in complex environments.
Innovation Solution
A control method that combines feedforward and feedback control by using a six-dimensional sensor and an admittance controller to calculate feedforward and feedback angular velocities, allowing proactive balance maintenance and restoration through joint motor control.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If feedback control is used to maintain static balance, then the robot can restore balance after deviation, but the response always lags behind external interference
Solution Approach 1:
The patent applies preliminary action by using a feedforward controller that predicts external interference forces before they cause significant balance deviation. The controller calculates predicted interference forces based on current state information and proactively generates compensatory torque commands, allowing the robot to counteract disturbances before they fully manifest as balance errors, thus reducing response lag while maintaining reliability
2Reliability
If feedback control is used, then balance can be restored after deviation, but the control quantity can only be adjusted after deviation occurs
Solution Approach 1:
The patent implements a dual-control architecture that combines feedback control with feedforward control. The feedback controller continuously monitors actual balance deviations and generates corrective commands based on measured errors, ensuring reliable balance restoration. Simultaneously, the feedforward controller uses predicted interference forces to proactively adjust control quantities before deviations occur, significantly improving control responsiveness while maintaining the effectiveness of feedback correction
3Device complexity
If traditional inverted pendulum model is used, then control implementation is simplified, but the robot cannot realize deviation control in complex environments
Solution Approach 1:
The patent enhances the traditional inverted pendulum model by introducing dynamic parameter adaptations. The system uses a six-dimensional force sensor to measure actual external interference forces and torques, then dynamically adjusts control parameters including feedforward gain coefficients and impedance parameters. This allows the controller to adapt to varying environmental conditions and interference characteristics, significantly improving anti-interference capability while maintaining the computational efficiency of the inverted pendulum framework
Data Source
AI summary
The present disclosure provides a humanoid robot and its control method and computer readable storage medium. The method includes: obtaining a current torque of a sole of the humanoid robot, an inclination angle of the sole, an inclination angle of a first joint of the humanoid robot, and an inclination angle of a second joint of the humanoid robot; calculating current feedforward angular velocities of motors of the first and second joints through the obtained information; calculating feedback angular velocities of the motors of the first and second joints; and obtaining inclination angles of the joints based on the feedforward angular velocities of the motors and the feedback angular velocities of the motors, and performing, through the motor of the second joint, a deviation control on the joints according to the inclination angles of the joints.