An Improved Spanning Tree-Based Algorithm for Coverage of Large Areas Using Multi-UAV Systems
Jan Chleboun, Thulio Amorim, Ana Maria Nascimento, Tiago Nascimento
Abstract
In this work, we propose an improved artificially weighted spanning tree coverage (IAWSTC) algorithm for distributed coverage path planning of multiple flying robots. The proposed approach is suitable for environment exploration in cluttered regions, where unexpected obstacles can appear. In addition, we present an online re-planner smoothing algorithm with unexpected detected obstacles. To validate our approach, we performed simulations and real robot experiments. The results showed that our proposed approach produces sub-regions with less redundancy than its previous version.
Topics & Concepts
Computer scienceSpanning treeRedundancy (engineering)Minimum spanning treePlannerSmoothingMotion planningRobotTree (set theory)AlgorithmPath (computing)Mobile robotArtificial intelligenceComputer visionMathematicsComputer networkMathematical analysisCombinatoricsOperating systemRobotic Path Planning AlgorithmsRobotics and Sensor-Based LocalizationDistributed Control Multi-Agent Systems