적응형 부호거리장 기반 확률 맵을 활용한 로드맵 구축 = Roadmap Construction Using Adaptive Signed Distance Field-based Probabilistic Maps

다국어 초록 (Multilingual Abstract)

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다국어 초록 (Multilingual Abstract)

Recently, path planning has been studied using a disk-graph probabilistic roadmap (DGPRM) with nodes and edges defined within a safe disk area. Unlike the probabilistic roamap(PRM) method, which requires numerous nodes and edges, the DGPRM method guarantees a high success rate of path planning even with fewer nodes. However, the conventional DGPRM method has the drawback of slow graph expansion owing to the probabilistic map and graph construction method. To overcome this limitation, we report proposes an improved DGPRM construction method that utilizes an adaptive signed distance field (SDF)-based probabilistic map and a modified graph construction approach. Because the SDF function can generate a probabilistic map based on the distance from the obstacle, larger disks can be generated first, resulting in efficient roadmap construction with fewer nodes. Additionally, by improving the graph construction method, a faster roadmap can be developed with fewer samples. To verify the feasibility of the proposed method, simulations were performed in various environments composed of grid maps, and the results were analyzed.