In the beginning, the balance control strategy used by biped robots was "staTIc walking". The characteristic of this strategy is that during the robot walking process, the projection of the center of gravity (COG) is always located in the support region. The advantage of this control strategy is that the robot can stop during the walking action. Do not fall, but at the cost of very slow movements (10 seconds or more per step, because the projections that need to maintain the center of gravity are always in the support area, otherwise it will be unstable).
Because static walking is far from human expectations, humans have developed another walking balance strategy, "dynamic walking." In dynamic walking, the robot's speed of action is increased to no more than 1 second per step. However, the drawbacks are also obvious. It is difficult for the robot to immediately stop in the state of motion (the effect of inertia), so that the robot becomes unstable during the state transition. In order to solve the effect of inertia, a zero moment point (ZMP) has been introduced into this control strategy. In the one-legged support phase, ZMP = COG. The advantage is that when the ZMP is strictly present in the support area of ​​the robot, the robot will never fall.
The mainstream of bipedal balance - dynamic walking based on ZMP
The mainstream of biped balance is now using ZMP-based dynamic walking. From the above basic content, one leg of the biped robot can be abstracted into the most basic "inverted pendulum" model in the control system.
Since the bipedal balance of complex terrain cannot be achieved by a single controller, the switching strategies of multiple controllers are used to solve the balancing problem. In this strategy, the robot's walking is set to a cycle. Each cycle is divided into different stages, as shown in the following figure:
Upright Pose Controller
This kind of controller keeps the robot in an upright position in the sloping terrain, thus maintaining the balance of the entire body. For biped robots, the measurement of the “global tilt angle†of the sloped terrain is particularly important. A commonly used measurement method is to install a 2-axis accelerometer inside the body of the robot, and a low-pass filter to form an inclinometer.
For the pitch attitude control of the robot, the vertical attitude controller adds a PI controller with pitch error on the specified ankle trajectory:
The upright attitude controller can be implemented by the following equation:
The figure below more intuitively reflects the difference in balance control before and after using the controller:
The figure below shows the difference in balance between the roll control before and after using the controller:
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