Enhancing Multi-Robot Formation Control and Navigation Using Virtual Structures and Improved Path Planning Algorithms

Abstract

Formation control plays a fundamental role in many domains, such as autonomous vehicles, aerial vehicles, and robotics, by enabling coordinated movement and cooperation among multiple agents. In this paper, we examine the performance of the Virtual Structure Approach (VSA) for formation control in robotic navigation, focusing on tasks like path planning based on an improvised A* algorithm and rectangular structure determination. Experimental validation with four mobile robots demonstrates the accuracy of the VSA in coordinating collaborative robot behavior. The proposed approach improves safety and efficiency in trajectory navigation. Additionally, improvements to the A* algorithm result in improved trajectories, which produce simplified pathways that facilitate efficient movement. The paper also explores the use of Lidar sensors and the Monte Carlo Localization technique to precisely map robot surroundings, improving perception and understanding of the surrounding environment. This work provides insightful information about formation control and opens up new possibilities for improving robotic navigation in many real-world contexts.