Obstacle avoidance of a wheeled robotic swarm using virtual spring-damper mesh

Author:

Wiech JakubORCID

Abstract

AbstractSwarm robotics, in which groups of robots coordinate to achieve a common goal, has the potential to revolutionize a wide range of industries. However, one of the key challenges in developing effective swarm systems is enabling the robots to navigate around obstacles while maintaining cohesion. In this article, the problem of trajectory tracking for a self-organized swarm of wheeled robots in the shape of a regular polygon operating in an environment with obstacles is addressed. The goal is for the swarm to follow a reference point by the geometric center of the swarm, while avoiding collision with obstacles and maintaining a given distance between neighboring robots and the reference point. To solve this problem, a method based on virtual forces that act on each individual robot in the swarm is proposed. These virtual forces are derived from virtual spring-damper connections acting from the obstacles, adjacent robots, and the reference point. The virtual forces allow the robots to dynamically adjust their trajectories to avoid obstacles and maintain the shape of the swarm. The proposed approach is evaluated through simulation and experiment with a swarm of two-wheeled robots. During the experiment the maximum deviation of inter-robot distances was equal to 0.08 m. With the set limit distance to obstacles equal to 0.2 m, from which virtual forces start to push the robot away from the edge of the obstacle, the shortest distance to obstacles was 0.11 m. The results demonstrate the effectiveness of the method in enabling the swarm to accurately follow the reference point while avoiding obstacles and maintaining the desired distances between robots. Overall, the approach represents a step forward in the development of virtual force-based algorithms for obstacle avoidance in swarm robotics.

Publisher

Springer Science and Business Media LLC

Subject

Electrical and Electronic Engineering,Control and Optimization,Mechanical Engineering,Modeling and Simulation,Civil and Structural Engineering,Control and Systems Engineering

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