The automatic obstacle avoidance of the AGV car mainly relies on the obstacle avoidance sensor and the obstacle avoidance control algorithm. Therefore, when the AGV is small and cannot automatically avoid obstacles, the fault problem we have to consider is the obstacle avoidance sensor and algorithm. The following are the Analysis of the failure causes that some AGVs cannot automatically avoid obstacles:
1. Sensor failure
In principle, no sensor is perfect. For example, the AGV car is in front of a piece of completely transparent glass. If infrared, lidar or vision solutions are used, the detection may fail because the light directly passes through the glass. need ultrasonic sensors
to detect obstacles. Therefore, in the process of real application, we definitely need to adopt a combination of various sensors, conduct a cross-validation of the data collected by different sensors, and integrate information to ensure that the AGV car can work stably and reliably.
In addition, there are other modes that may cause the sensor to fail, such as ultrasonic ranging, which generally requires an ultrasonic array. If the sensors between the arrays work at the same time, they will easily interfere with each other. The light waves emitted by sensor A are reflected back and received by sensor B. , resulting in errors in the measurement results, but if you work in sequence one by one, because the sampling period of the ultrasonic sensor is relatively long, it will slow down the speed of the entire acquisition and affect real-time obstacle avoidance, which requires the structure of the hardware to the algorithm. All must be designed to increase the sampling speed as much as possible and reduce the crosstalk between the sensors.
For example, if the AGV car needs to move, it generally needs a motor and a driver. They will have capacitive compatibility problems during their work, which may lead to errors in sensor acquisition, especially for analog sensors. Therefore, in the implementation of In the process, the motor driver and other equipment, the acquisition part of the sensor, and the power communication part should be kept isolated to ensure that the entire system can work normally.
2. Algorithm design
In the several algorithms just mentioned, many of them did not fully consider the kinematic model and dynamic model of the entire AGV car itself in the design. The trajectory planned by such an algorithm may not be kinematically realized. It may be possible to achieve kinematics, but it is very difficult to control. For example, if the chassis of an AGV car is the structure of a car, it cannot be turned on the spot, or even if the AGV car can be turned on the spot. , But if we make a big maneuver all at once, our entire motor cannot be executed. Therefore, when designing, it is necessary to optimize the structure and control of the AGV car itself, and when designing an obstacle avoidance scheme, the feasibility problem must also be considered.
Then when designing the architecture of the entire algorithm, we must consider that in order to avoid or avoid hurting people or hurting the AGV car itself, when performing work, obstacle avoidance is a relatively high priority task, or even a task, and its own The priority of operation and the control of the AGV car are also given priority. At the same time, the algorithm must be implemented fast enough to meet our real-time requirements.
In short, obstacle avoidance can be regarded as a special case of AGV car in autonomous navigation planning to a certain extent. Compared with the overall global navigation, it has higher requirements for real-time and reliability, and then, locality and dynamic. Sexuality is one of its characteristics, which we must pay attention to when designing the hardware and software architecture of the entire AGV car.
