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The performance of the two well-known algorithms, A* and Dijkstra, was studied in this research within the swarm robotics framework, focusing on the coordinated interaction of several autonomous agents. In this study, simulation with ROS2 tools and Gazebo were used to assess these algorithms’ performance under various conditions, including non-changing environments as well as environments undergoing dynamic changes. A customized robotic model based on the Unified Robot Description Format is applied as a basis for navigation, and the work also incorporates SLAM techniques to improve the accuracy of navigation. In this study, distinct characteristics and operation efficiency were found between the A* and Dijkstra algorithms, providing insights that can potentially enhance path planning strategies in practical applications of swarm robots.

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Analysis of Path Planning Algorithms for Swarm Robots

  • 会议论文

  • 发表日期：

    2026年

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  • N. R. Nithish Kumar,
  • T. N. Sivatmiga,
  • M. Sindhu

摘要

The performance of the two well-known algorithms, A* and Dijkstra, was studied in this research within the swarm robotics framework, focusing on the coordinated interaction of several autonomous agents. In this study, simulation with ROS2 tools and Gazebo were used to assess these algorithms’ performance under various conditions, including non-changing environments as well as environments undergoing dynamic changes. A customized robotic model based on the Unified Robot Description Format is applied as a basis for navigation, and the work also incorporates SLAM techniques to improve the accuracy of navigation. In this study, distinct characteristics and operation efficiency were found between the A* and Dijkstra algorithms, providing insights that can potentially enhance path planning strategies in practical applications of swarm robots.