Water Saving Control of Turfgrass Irrigation Robot Using Genetic Simulated Annealing Algorithm

Abstract

Artificial intelligence through the robotic system offers a solution to the quest for an autonomous system with high cutting efficiency for lawn mowing. Because of the current trimming and maintenance operations on grasslands and gardens, it is essential to develop autonomous and efficient lawn pruning electromechanical equipment. This paper describes the design and construction of a high-performance automated grass trimming and irrigating robot. This device cuts and irrigates grass automatically with little human intervention. A genetic simulated annealing algorithm was employed to optimize motor parameters, specifically design a set of mowing mechanisms and mowing height adjustment system. The prototype was tested, which mainly includes the running status evaluation of the walking module, the mowing module, the cutter head lifting module, and the collision detection module. This robot can save water while watering the lawns, reduce labor costs, and improve mowing efficiency. We note that the proposed system can be implemented on a large scale under natural conditions in the future, which will be helpful in robotics applications and cutting grass on lawns and playing grounds.