A general legged locomotion controller must integrate both posture control and rhythmic motion control and have the ability to shift continuously from one control method to the other according to locomotion speed.
Simulation and experiment results show that fast, accurate, and robust performance is obtained for the posture control of six-legged walking robots using the NFTSM controller.
And a novel command limiting tracking differentiator (CLTD), which considers not only the controlled but also uncontrolled state constraints, is specially designed for posture control.
Since for posture guidance the posture control system has to be known, a simple approach for identification of the controller parameters is proposed.
This paper also presents a body posture control method.
This work presents an attempt of integrating a learned predictor into a humanoid posture control.
The artificial muscle model was utilized for the posture control of a biomimetic underwater robot.
Second, a foot-force distribution model and a compensation model are built to achieve posture control.
A model-based control structure is preferred in order to implement the posture control algorithm to the robot control.
Posture control models are instrumental to interpret experimental data and test hypotheses.
The rabidity, accuracy, and robustness of posture control are important for enhancing the posture changing ability.
