1. Mobile robot motion control
"The world's martial arts, only fast is not broken", mobile robots generally control the wheels through the motor to complete the movement. As the end actuator, the motion control of the motor requires fast response (millisecond-level echo time) and high precision. At present, the typical motor control is a cascade control system, which consists of three closed-loop feedbacks, namely the azimuth ring, the speed loop, and the current loop.
OK, the control module is essentially three PIDs nested, so easy. The teacher told us that more than 90% of the current control system uses PID, because PID is really robust. In addition, regarding the automatic wheel motor of mobile robots, the speed of the motor is often controlled by the control of the motor speed, and there is no external azimuth ring at this time, only two rings of speed ring and current ring are required.
2. Robot motion model
The model is the foundation of the whole control system, and the robot motion model depicts the connection between the speed of the automatic wheel rotation of the mobile robot and the overall motion of the robot. There are three common robot motion models: single steering wheel, dual wheel differential, and dual steering wheel.
3. Path stalking
In the classic tracking problem in control theory, that is, given a track, the mobile robot needs to walk along the track as much as possible, and the control policy is to minimize the error between the actual walking route of the robot and the planned track.
* The simple way to complete the way tracking is to feedback the idea of manipulation, that is, to obtain the error Δα of the tangent direction of the current robot motion direction and the orbit curve, and to obtain the distance error Δβ between the robot motion center and the orbit curve, and introduce the two into the closed-loop control as feedback quantities, and calculate the required linear velocity and angular velocity with a certain share control rate.
4. Multi-machine scheduling
In actual scenarios, multiple robots are often required to process complex multiple tasks online at the same time, and the multi-machine scheduling system needs to optimize the walking path of each mobile robot to avoid deadlocks, that is, the paths are occupied by each other and cannot be released autonomously.
In addition to meeting the basic requirements of no deadlock, the multi-machine scheduling system also needs to reasonably allocate tasks to each mobile robot to improve the overall task performance efficiency, and at the same time select the right time to allocate idle mobile robots for automatic charging.
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