Two-Stage Path Planning for Long-Distance Off-Road Path Planning Based on Terrain Data

Bibliographic Data

ID22032847
AuthorsXudong Zheng (0000-0001-5403-8862, National University of Defense Technology), Mengyu Ma (0000-0002-7510-5638, National University of Defense Technology), Zhinong Zhong (National University of Defense Technology, corresponding author), Anran Yang (0000-0001-6106-759X, National University of Defense Technology), Luo Chen (0000-0003-2665-6086, National University of Defense Technology), Ning Jing (0000-0003-3445-6658, National University of Defense Technology)
Year2024
Volume13
Issue6
Pages184
Publication date2024-05-31
Open AccessYes
TypeARTICLE
VenueISPRS International Journal of Geo-Information (JOURNAL)
Journal identifiersISSN: 2220-9964 • E-ISSN: 2220-9964
PublisherMDPI AG (PUBLISHER • IT)
DOI10.3390/ijgi13060184
OpenAlexW4399208389
LanguageEN
References cited27

In the face of increasing demands for tasks such as mountain rescue, geological exploration, and military operations in complex wilderness environments, planning an efficient walking route is crucial. To address the inefficiency of traditional two-dimensional path planning, this paper proposes a two-stage path planning algorithm. First, an improved Probabilistic Roadmap (PRM) algorithm is used to quickly and roughly determine the initial path. Then, the morphological dilation is applied to process the grid points of the initial path, retaining the surrounding area of the initial path for a precise positioning of the search range. Finally, the idea of the A∗ algorithm is applied to achieve precise path planning in the refined search range. During the process of constructing the topology map, we utilized parallelization acceleration strategies to expedite the graph construction. In order to verify the effectiveness of the algorithm, we used terrain data to construct a wilderness environment model, and tests were conducted on off-road path planning tasks with different terrains and distances. The experimental results show a substantial enhancement in the computational efficiency of the proposed algorithm relative to the conventional A∗ algorithm by 30 to 60 times

Any-angle path planning · Cartography · Computer network · Geography · Motion planning · Terrain · Computer Science · Robotic Locomotion and Control · Robotic Path Planning Algorithms · Robotics and Sensor-Based Localization · Artificial Intelligence · Geology

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