Design of Intelligent Path-finding Algorithm for Sweeping Robot Based on BP Neural Network Model

Cleaning is a repetitive and time-consuming job. Although there are many kinds of vacuum cleaners that can make people get rid of the traditional cleaning tools, they still can’t get rid of the cleaning work, and these vacuum cleaners still have great limitations. With the continuous development and progress of technology, the general trend of artificial intelligence (AI) is coming. As a contemporary intelligent household appliance, sweeping robot has more and more applications. In this paper, the full coverage intelligent path-finding algorithm is designed and optimized, and an intelligent path-finding algorithm of sweeping robot based on improved Back-propagation neural network (BPNN) is proposed, so as to optimize the sweeping path of sweeping robot, select the best cleaning path and eliminate the cleaning blind area of sweeping robot as much as possible. Finally, the proposed algorithm and the traditional ACO algorithm are simulated and compared. The experimental results show that the algorithm in this paper can not only be well applied in closed unknown complex environment, but also has the advantages of few local sub-regions, short and smooth path, and also has good adaptability and real-time optimization characteristics.