<![CDATA[This study introduces an innovative combined system utilizing the Robot Operating System (ROS) to enhance multi-robot systems for comprehensive coverage in indoor settings. The research emphasizes integrating diverse robotics technologies, such as map partitioning, path planning, and adaptive task allocation, to boost deployment and coordination for localization and navigation. The system uses occupancy grid maps for effective map partitioning and employs a market-based algorithm for adaptive task distribution. A hybrid path planning approach, merging Boustrophedon Traversing Coverage (BTC) and Spiral Traversing Coverage (STC), ensures complete area coverage while reducing redundancy. During thorough testing, our system showed coverage efficiencies between 94% and 98% in different layouts and conditions, with task completion rates as high as 19.6% per minute, highlighting its ability to effectively handle and adjust to various indoor environments. Additionally, dynamic robot deployment in response to environmental changes has led to enhanced operational efficiency and flexibility. The initial results are promising, though future research will focus on incorporating dynamic obstacle management and path planning to boost the system's robustness and adaptability. This study paves the way for further exploration and development of advanced path-planning algorithms to enhance the performance and usability of multi-robot systems in dynamic environment applications.]]>
Copyrights © 2024
