Development of an Autonomous Solar Grass Cutting Robot with a Path Memorizing Mechanism

Abstract

Grass maintenance has typically been done by hand or with fossil fuel-powered machinery, which presents efficiency and environmental concerns. The proposed system examines these difficulties by creating an autonomous solar grass-cutting robot with a path-memorizing mechanism. Unlike traditional approaches, the innovative remedy improves lawn maintenance efficiency and sustainability by combining autonomous robotics and renewable energy sources. The robot uses advanced technology such as LiDAR, cameras, and neural networks to navigate and memorize optimal mowing patterns, increasing grass-cutting efficiency and coverage. Furthermore, using a solar power system with energy storage technology provides long-term operation without the need for fossil fuels. Compared to existing systems, the results show higher performance in terms of efficiency (95%), control complexity (10 signals), and grass-cutting quality (high uniformity and outstanding precision). The study represents an essential development in automated lawn maintenance technology, providing a viable alternative for effective and environmentally friendly grass management procedures.