A Cooperative Motion Method for Swarm Robots in Scenes with Obstacles

Abstract

The invention relates to the technical field of robots, more particularly to a cooperative motion method for a robot cluster in an obstacle scene. The method provided by the invention is used for enabling multiple robots to realize formation transformation, dynamic and static obstacle avoidance and cooperative motion in the obstacle scene. The method defines the cooperative control of the robot cluster in a complex environment as a distributed model predictive control problem. Each robot solves an optimization equation independently based on the information of local neighbors, which has betterrobustness and flexibility. At the same time, the method proposes the concept of a formation diagram, and uses a directed diagram to represent the robot formation. Under the premise of ensuring the connectivity of the diagram, local transformation of the desired formation can be realized by changing the edges and weights of the formation, and at the same time, the connectivity and the flexibilityof the cluster can be ensured. Besides, the method provided by the invention has a hierarchical structure. By adopting the hierarchical structure, the coupling between modules can be reduced, and algorithm design and expansion can be facilitated.

Description

technical field [0001] The invention relates to the technical fields of swarm intelligence and robot control, and more particularly, to a method for cooperative movement of swarm robots in a scene with obstacles. Background technique [0002] With the continuous development of robotics, automated robotic systems play an important role in more and more fields, such as industrial robots, household robots, service robots and so on. Therefore, automatic navigation of robots in structured environments has been a hot research area. Compared with traditional human systems, robotic systems have many advantages, such as economy, time and safety. Compared with single-robot systems, multi-robot systems have greater advantages and broader application scenarios, such as exploration in hazardous environments, monitoring in agriculture, and military missions under extreme conditions. For the same complex task, a multi-robot system can be completed more efficiently and with lower cost tha...

AI Technical Summary

Problems solved by technology

However, in a scene with obstacles, the robot cluster cannot move in a fixed formation, and the above method is not fully applicable at this time

In a constrained environment, the robot swarm should adaptively change the expected formation according to the environmental information detected by the sensor, but how to choose a new formation and how to realize the formation transformation is a challenging problem. For the distributed architecture For clusters, the problem is more complicated

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