Power-Optimized Information Systems for Mobile Robotics in Physical Processes

This paper explores the integration of Autonomous Mobile Robots (AMRs) in industrial settings, revolutionizing task scheduling. Focused on minimizing operational completion time, it delves into the physical processes within information systems. The study emphasizes the hardware, software, and robotics intersection, providing an overview of key AMR components and their role in task execution. Mobility, sensing capabilities, and interaction with the environment are crucial considerations for effective scheduling algorithms. Real-time data acquisition through AMR-mounted sensors informs scheduling algorithms, emphasizing the importance of accurate information. Data storage's pivotal role in maintaining efficiency is highlighted, stressing quick retrieval for rapid decision-making. The study examines central processing units (CPU) and arithmetic logic units (ALU) roles in processing scheduling algorithms, emphasizing the need for computational power. Communication processes, network communication, and data transmission reliability are paramount for coordinating multiple AMRs. Power supply and cooling systems' significance in sustaining AMR infrastructure is explored, addressing electrical power provision and environmental controls. Physical security measures and maintenance processes, including hardware and software updates, ensure peak AMR efficiency. In conclusion, this research illuminates the integral physical processes within information systems for AMR-based task scheduling, offering insights for enhanced efficiency in diverse industrial settings.