Advanced Navigation Control Systems for Autonomous Mobile Robots Utilizing 3D Lidar Technology
| Authors | Gundreddi Deepika Reddy1 , Nageswara Rao Medikondu1 , Prakash Babu Kanakavalli2 , Vinjamuri Venkata Kamesh3 , T. Vijaya Kumar1 |
| Affiliations |
1Department of Mechanical Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, 522302 Guntur, India 2Department of Mechanical Engineering, Velagapudi Ramakrishna Siddhartha Engineering College, Siddhartha Academy of Higher Education Deemed to be university, Kanur, 520007 Vijayawada, India 3Department of Mechanical Engineering, Aditya University, Surampalem, East Godavari District, 533437 Andhra Pradesh, India |
| Е-mail | medikondu1979@gmail.com |
| Issue | Volume 16, Year 2024, Number 4 |
| Dates | Received 18 April 2024; revised manuscript received 15 August 2024; published online 27 August 2024 |
| Citation | Gundreddi Deepika Reddy, Nageswara Rao Medikondu, et al., J. Nano- Electron. Phys. 16 No 4, 04015 (2024) |
| DOI | https://doi.org/10.21272/jnep.16(4).04015 |
| PACS Number(s) | 01.50.hv, 07.05.Hd |
| Keywords | Sensor-based navigation, Access point selection, Industry 4.0, Sensor fusion Real-time decision making and Path optimization. |
| Annotation |
This paper outlines a novel approach to developing navigation control systems for autonomous mobile robots utilizing 3D Lidar technology. By harnessing the capabilities of 3D Lidar sensors, robots can perceive their environment with remarkable precision, enabling them to navigate effectively in complex and dynamic surroundings. The proposed control framework encompasses a fusion of sensor data processing, localization algorithms, path planning strategies, and motion control mechanisms. Through the integration of these components, autonomous mobile robots can navigate diverse environments, both indoors and outdoors, with efficiency and safety. The use of 3D Lidar technology enhances the robots' perception capabilities, allowing them to generate detailed and accurate maps of their surroundings in real-time. Additionally, adaptive algorithms are incorporated into the control system to address uncertainties and dynamically changing obstacles encountered during navigation. Experimental results demonstrate the effectiveness and reliability of the proposed navigation control systems, highlighting their potential for various real-world applications such as warehouse logistics, surveillance, and search and rescue operations. |
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