Power-Optimized Information Systems for Mobile Robotics in Physical Processes

Authors Alla Venkata Ranga Surya Prasad1, Leela Santi Parige2, A. Chandra Sekhara Babu3, Vinjamuri Venkata Kamesh4, Nageswara Rao Medikondu5, Sudipta Das6

1Department of Mechanical Engineering, Koneru Lakshmaiah Education Foundation Vaddeswaram, 522302 Guntur, India

2Department of Mathematics and Statistics, Bhavan’s Vivekananda College of Science Humanities and Commerce. Sainikpuri, Secunderabad, 500094 Telangana, India

3Freshman Engineering Department, PVP Siddhartha Institute of Technology Kanur, 520007 Vijayawada, India

4Department of Mechanical Engineering, Aditya Engineering College (A), Surampalem, East Godavari District, 533437 Andhra Pradesh, India

5Department of Mechanical Engineering, Koneru Lakshmaiah Education Foundation Vaddeswaram, 522302 Guntur, India

6Department of Electronics and Communication Engineering, IMPS College of Engineering and Technology, 732103 Malda, West Bengal, India

Е-mail medikondu1979@gmail.com
Issue Volume 16, Year 2024, Number 1
Dates Received 15 December 2023; revised manuscript received 17 February 2024; published online 28 February 2024
Citation Alla Venkata Ranga Surya Prasad, Leela Santi Parige, A. Chandra Sekhara Babu, et al., J. Nano- Electron. Phys. 16 No 1, 01015 (2024)
DOI https://doi.org/10.21272/jnep.16(1).01015
PACS Number(s) 07.50. – e
Keywords Information System, Optimization of Energy, Autonomous Mobile Robots, Best First Search.

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.

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