Dynamic processing of 2D maps used by search algorithms for trajectory planning

Shaymaa Alzubairi, Alexander Petunin, Hussam Alwan, Hussam Alwan

Abstract


Path planning has drawn a lot of attention in robotics research. Numerous algorithms have been developed to overcome path planning's challenges. Seldom do researchers test algorithms on reality-like maps; instead, they test algorithms on randomly and regularly programmed maps. Because realistic maps can have a variety of obstacles with varying sizes and forms as well as sharp corners, they are highly dependable for testing algorithms. In the meanwhile, morphological operations and image processing domains might be the focus of research when genuine maps are used. These maps can also be time-consuming and require extra work to create. This paper suggests a straightforward and dynamic approach to effective read and process 2D maps so that different algorithms can recognized them. Simulations were conduct on two realistic maps to demonstrate the merits of the proposed method, and the probabilistic roadmap (PRM) algorithm was chosen to plan a path on these maps. In all simulations, the proposed method successfully read and processed the map in an average of 1.50 s. Moreover, PRM quickly recognized boundaries, obstacles, and free space on the maps and planned a collision-free route from the starting point to the destination.

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References


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