UNMANNED LEAF SWEEPING AND CRUSHING VEHICLE

Abstract

In urban and campus environments, fallen leaves accumulate extensively. The research team has developed an unmanned leaf sweeping vehicle to improve cleaning efficiency and reduce labor costs. The innovative features of this unmanned leaf sweeping vehicle lie in its unmanned driving software technology and built-in navigation function. The hardware design adopts corrosion-resistant hard materials, high-speed and energy-saving motors, adjustable cleaning brushes, vacuum cleaners, and large-capacity lithium batteries, enabling the sweeping vehicle to achieve intelligence, high performance, high efficiency, energy saving, and environmental protection. The core contents of the unmanned leaf sweeping vehicle include: control of driving speed and sweeping speed; calculations for movement and sweeping to minimize leaf sweeping time and movement path; mathematical model prediction; real-time sensor feedback; intelligent machine learning; and predicted movement path. The control system includes driving control, sweeping control, and crushing control. The motor provides power, the ball screw converts motion, and the sensor provides real-time feedback. Autonomous navigation technology and deep learning algorithms are introduced to enhance intelligence. Users can control the vehicle and realize remote monitoring through a mobile phone APP.