Intelligent mobile robot multi-vehicle cooperative control floating system and control method thereof

Abstract

The invention provides an intelligent mobile robot multi-vehicle cooperative control floating system and a control method thereof. The intelligent mobile robot multi-vehicle cooperative control floating system comprises a floating control module; the floating control module comprises a floating control unit and a floating adjusting device, and the floating control unit comprises a camera, an angleencoder and a limiting switch; the camera is used for collecting floating quantity deviation of the floating adjusting device in the x direction, the y direction and the z direction, the angle encoder and the limiting switch are used for collecting floating quantity information of the floating adjusting device and transmitting the information to an AGV motion controller, and the AGV motion controller is in signal connection with a navigation positioning module, a driving module and an alarm module. According to the multi-vehicle cooperative control floating system of the intelligent mobile robot and the control method of the multi-vehicle cooperative control floating system, system resource consumption can be reduced, communication errors can be reduced, cooperative control over multipleAGVs is more efficient and stable in operation, and the multi-vehicle cooperative control system plays a greater role in an intelligent factory.

Description

technical field [0001] The invention belongs to the technical field of multi-vehicle linkage of an intelligent mobile robot, and in particular relates to an intelligent mobile robot multi-vehicle cooperative control floating system and a control method thereof. Background technique [0002] With the wave of intelligent manufacturing sweeping the world, the degree of automation of the material transportation process is an important indicator to measure the level of intelligence and modernization of the manufacturing industry. The multi-vehicle linkage of intelligent mobile robots (AGV) has extremely high application value in the fields of material transportation in smart factories. In the task of handling long-sized and overweight cargo, multi-vehicle linkage enables AGV to have better carrying capacity, wear resistance and driving efficiency. However, there is a problem of collaborative control among multiple AGV drive units. Due to the rigid constraints of the robot body, s...

AI Technical Summary

Problems solved by technology

However, there is a problem of collaborative control among multiple AGV drive units. Due to the rigid constraints of the robot body, some drive units cannot perform path tracking control completely according to their own current path deviation state.

The existing motion control methods are based on the traditional PID algorithm, which integrates various control algorithms such as neural network and genetic algorithm to adaptively adjust the PID parameters. This method can improve the anti-interference ability and accuracy of AGV during operation. Tracking ability, but this type of algorithm increases the complexity of the system motion model, the difficulty of controller design is greatly increased, and it is difficult to guarantee stable operation

In addition, in a system composed of multiple AGVs, the inter-vehicle communication has a delay and there are communication errors, resulting in the inability of better coordinated control between multiple vehicles and the inability to play the value of the multi-AGV system

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