Simultaneous Map Generation and Localization for an Autonomous Mobile Robot Using the MOORA Method

Introduction: Autonomous mobile robots (AMRs) represent a transformative technology revolutionizing various industries, from manufacturing and logistics to healthcare and service sectors. These robots, equipped with advanced sensors, artificial intelligence (AI), and navigation systems, can operate independently in dynamic environments without human intervention. The emergence of AMRs has significantly impacted traditional workflows, offering enhanced efficiency, flexibility, and safety in diverse operational settings. The development of AMRs stems from the increasing demand for automation solutions to address challenges such as labor shortages, rising operational costs, and the need for faster and more accurate task execution. Unlike traditional industrial robots confined to fixed locations or predefined paths, AMRs possess the capability to navigate complex environments, adapt to changing conditions, and collaborate seamlessly with humans and other machines. The significance of research in the field of autonomous mobile robots (AMRs) extends across various domains, reflecting their transformative impact on industries, economies, and society as a whole. Understanding the importance of research in this field is essential for harnessing the full potential of AMRs and addressing the challenges and opportunities they present. Technological Advancements: Research in AMRs drives technological advancements, leading to the development of more sophisticated sensors, AI algorithms, and navigation systems. These advancements enhance the capabilities of AMRs, enabling them to operate in complex and dynamic environments with greater autonomy, efficiency, and safety. Industrial Automation: AMRs play a crucial role in industrial automation, revolutionizing manufacturing, warehousing, and logistics operations. Research in this area focuses on optimizing AMR deployment, task allocation, and coordination to improve productivity, reduce costs, and streamline processes in diverse industrial settings. Robo Navigator 3000, Auto Rover X, Smart Path Pro, Nav Bot Elite, Intelli Scout. Battery Life (hours), Navigation Accuracy (%), Maintenance Requirement (Rating), Noise Level (dB). The results indicate that Smart Path Pro achieved the highest rank, while Auto Rover X received the lowest rank being attained. “The value of the dataset for Autonomous Mobile Robot lies, according to the Weighted Sum Method (WSM), demonstrates that Smart Path Pro achieves the highest ranking.”