A Comprehensive Study on UGV’s with Future Applications in Space and Agriculture

Recent progress in semi-autonomous robotic systems marks a notable transition from manual hardware control to integrated, intelligent frameworks. The development of the web-controlled rover highlights the success of combining modular embedded hardware with local server hosting to achieve real-time monitoring and environmental sensing. While studies by Miao et al. [2] and Zhang et al. [1] emphasize the importance of path-planning and traversable tolerance, this project demonstrates that a cost-effective synthesis of Raspberry Pi and Arduino Uno can effectively handle high-level decision-making and real-time motor actuation. Collectively, the implementation suggests that hybrid control architectures, which utilize serial communication and cloud-based data persistence through Firebase, outperform traditional standalone robotic setups in terms of scalability and remote accessibility. Despite these technical advancements, challenges related to hardware reliability, sensor noise in the MPU6050, and power fluctuations persist. Future research should focus on optimizing low-latency data flow and implementing more robust fault-tolerance protocols to make autonomous exploration more practical for real-world environmental monitoring. In summary, the shift toward demand-based irrigation logic (ADBI) and real-time visual feedback has greatly advanced the reliability of small-scale robotic platforms, paving the way for next-generation exploration systems that promise enhanced usability and wider applicability in both agricultural and research environment.

1.       H. Zhang, F. Jiang, and Q. Li, "An improved path planning and tracking control method for planetary exploration rovers with traversable tolerance," Biomimetic Intelligence and Robotics, vol. 5, no. 2, 2025. 2.       Q. Miao et al., "A Comprehensive Review of Path-Planning Algorithms for Planetary Rover Exploration," IEEE Access, vol. 13, pp. 15632-15659, 2025. 3.       C. Pace, "Simulating and Training Autonomous Rover Navigation in Unity Engine Using Local Sensor Data," Senior Honors Thesis, Liberty University, 2024. 4.       S. H. K. Mohamed, et al., "AI in Space Exploration: Autonomous Systems for Planetary Rovers and Satellite Data Analysis," 2024 International Conference on Computation, Automation and Knowledge Management (ICCAKM), Dubai, United Arab Emirates, 2024, pp. 16. 5.       Mazumder, B. J. S. B. E. Grinberg, and J. L. Vian, "L-VITEX: Light-Weight Visual Intuition for Terrain Exploration," in Proc. IEEE/CVF Winter Conf. Appl. Comput. Vis. (WACV), pp. 8835-8844, JAN. 2024. 6.       A. Christian, "A Comprehensive Review of Terrain Sensing and Classification Techniques for Autonomous Planetary Rovers," Robotics, vol. 13, no. 1, p. 1, 2024. 7.       M. Salinas-Camus, C. Kulkarni, & M. Orchard, "Battery State-of-Health Aware Path Planning for a Mars Rover," in Annual Conference of the PHM Society, vol. 15, no. 1, 2023. 8.       R. Pathirana et al., "Innovative rover systems for planetary exploration: integrating enhanced Mobility, miniaturization, and robotic sampling techniques in the Asia Pacific context," Acta Astronaut., vol. 206, pp. 146-163, MAY. 2023. 25 9.       X. Jin et al., "Physical Reservoir Computing in Hook-Shaped Rover Wheel Spokes for Real Time Terrain Identification," Nat. Commun., vol. 14, no. 1, Art. no. 2185, APR. 2023. 10.    L. Feng et al., "An Instrumented Wheel-On-Limb System of Planetary Rovers for Wheel Terrain Interactions: System Conception and Preliminary Design," Aerospace, vol. 10, no. 3, Art. no. 238, MAR. 2023.