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The increasing implementation of autonomous robots in industries and daily life demands the development of a robust control algorithm that enables robots to perform their tasks successfully. Critical tasks such as rescue missions and area exploration require robots to work cooperatively in a formation to accomplish the tasks quickly. Moreover, the existence of obstacles in the environment requires all the robots' to rapidly process environmental changes to maintain the formation pattern. Thus, this paper introduces a distributed robot formation control system using the consensus algorithm that enables a group of robots to establish and maintain formations using only the local information of the robots. Furthermore, an obstacle avoidance algorithm based on the distance and angle between robots and obstacles is introduced to ensure safe navigation for the group of robots. The algorithm's effectiveness is demonstrated by a multi-robot system with randomly generated starting positions and velocities, where it is shown that the robots can agree on the control variables and establish the required formation while also avoiding obstacles in the environment.

The increasing implementation of autonomous robots in industries and daily life demands the development of a robust control algorithm that enables robots to perform their tasks successfully. Critical tasks such as rescue missions and area exploration require robots to work cooperatively in a formation to accomplish the tasks quickly. Moreover, the existence of obstacles in the environment requires all the robots' to rapidly process environmental changes to maintain the formation pattern. Thus, this paper introduces a distributed robot formation control system using the consensus algorithm that enables a group of robots to establish and maintain formations using only the local information of the robots. Furthermore, an obstacle avoidance algorithm based on the distance and angle between robots and obstacles is introduced to ensure safe navigation for the group of robots. The algorithm's effectiveness is demonstrated by a multi-robot system with randomly generated starting positions and velocities, where it is shown that the robots can agree on the control variables and establish the required formation while also avoiding obstacles in the environment.

No abstract