Research on path planning algorithm of mobile robot based on Dijkstra

The integration of automation technologies in warehouses has significantly transformed logistics operations, enhanced efficiency, and reduced labor costs. To address the limitations of traditional path-planning approaches, which often lack the ability to effectively handle dynamic environments and real-time data processing, this study presents an improved framework that integrates real-time image processing with an enhanced Dijkstra algorithm. This paper focuses on the development of a real-time path planning and obstacle avoidance system for mobile robots, utilizing an enhanced Dijkstra algorithm. Through the implementation of Canny edge detection and a dynamic point-setting algorithm, the system successfully navigates complex warehouse environments, adjusting paths in response to real-time data. Through this approach, the system significantly reduces computation time while maintaining high accuracy in obstacle detection and path planning. Experimental results demonstrate a substantial improvement in navigation efficiency, with the robot successfully avoiding obstacles and optimizing paths in various warehouse scenarios. The study contributes to the advancement of autonomous robotics in smart warehouses, offering a scalable and adaptable solution to meet evolving industrial needs.