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

Abstract Formation control is a fundamental aspect in various domains, including autonomous vehicles, aerial vehicles, and robotics, facilitating coordinated movement and collaboration among multiple agents. This paper investigates the effectiveness of the Virtual Structure Approach (VSA) for formation control in robotic navigation, with a specific focus on tasks such as rectangular structure determination and path planning based on an improvised A* algorithm. Experimental validation involving four mobile robots showcases the VSA's precision in orchestrating collaborative robot behavior. By seamlessly integrating VSA with traditional A* algorithmderived paths and collision avoidance mechanisms, the proposed approach enhances both safety and efficiency in trajectory navigation. Moreover, enhancements in the A* algorithm contribute to optimized trajectories, yielding streamlined paths conducive to efficient navigation. The study also delves into the utilization of the Monte Carlo Localization technique coupled with Lidar sensors to accurately map robot surroundings, thereby augmenting perception and environment comprehension. This research contributes valuable insights into the realm of formation control, offering promising avenues for advancing robotic navigation capabilities in diverse real-world applications.