Year: 2025
Type: article
Abstract: This paper presents a cost-effective robotic system capable of manual control via RF remote and autonomous navigation using GPS-based information. The system employs artificial intelligence to dynamically classify and avoid non-grass obstacles, ensuring safe operation in real environments. The prototype integrates affordable hardware including Arduino board, sensors, actuators and Raspberry Pi with lightweight algorithms to balance performance and cost. Experimental validation confirms its ability to follow predefined paths with ±1.5 meters deviation in open area and 90% obstacle avoidance success rate. With a total hardware cost under $200, this prototype highlights feasibility for larger-scale implementation.
DOI: 10.55003/eth.420305
Institution: King Mongkut's Institute of Technology Ladkrabang
Language: English
Topic: Smart Agriculture and AI
Subfield: Plant Science
Domain: Life Sciences
Open Access status: diamond
OpenAlex ID: W4414334948
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