A control method for group mobile internet of things robot

Abstract

The invention discloses a control method of group moving internet-of-things robots. According to the core idea, a control function of the internet-of-things robots is made to have time terms and becomes the function about time, and when time is changed, the control function is also changed; in addition, it is considered that different member work divisions and communication delay exist in the actual robot group, the robot individuals are allowed to be driven by different functions at the same time point, and algorithm flexibility is further increased; time serves as one of independent variables to be introduced into the control function of the internet-of-things robots, the control function is not single or fixed, and can be continuously changed along with time, the richer behavior selection is brought to the internet-of-things robot individuals, complex and changeable work needs are met, and the robots have the stronger environment adaptive capacity.

Description

technical field [0001] The invention relates to the field of robot control, in particular to a method for controlling a group mobile Internet of Things robot. Background technique [0002] With the increasing maturity of the Internet of Things technology, it is possible for large-scale Internet of Things robots to work together. Before that, problems such as task distribution and orderly group movement of robots also need to be solved urgently. Referring to natural organisms, it is not difficult to find that group behavior is a ubiquitous biological behavior pattern. Ant colonies can hunt insects that are much larger than themselves or build nests efficiently through collective cooperation. Formation, some fish in the ocean will cluster to avoid the threat of predators. These biological clusters do not seem to have a so-called "central system" to issue unified commands, but they can achieve a certain goal in an orderly manner, which is really amazing. Obviously, this natura...

AI Technical Summary

Problems solved by technology

Since then, a large number of swarm control algorithms have emerged, and various algorithms have been able to achieve rich group behavior control. However, in actual situations, a single control algorithm that is immutable often cannot meet the needs. In contrast, control algorithms that can change over time are more It is suitable for describing the working mode of the group system in the real environment, and also has a stronger ability to adapt to the environment

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