Details

Autor(en) / Beteiligte

• Tang, Gang
• Tang, Congqiang
• Claramunt, Christophe
• Hu, Xiong
• Zhou, Peipei

Titel

Geometric A-Star Algorithm: An Improved A-Star Algorithm for AGV Path Planning in a Port Environment

Ist Teil von

• IEEE access, 2021, Vol.9, p.59196-59210

Ort / Verlag

Piscataway: IEEE

Erscheinungsjahr

2021

Link zum Volltext

Quelle

EZB Free E-Journals

Beschreibungen/Notizen

• This research introduces a path planning method based on the geometric A-star algorithm. The whole approach is applied to an Automated Guided Vehicle (AGV) in order to avoid the problems of many nodes, long-distance and large turning angle, and these problems usually exist in the sawtooth and cross paths produced by the traditional A-star algorithm. First, a grid method models a port environment. Second, the nodes in the close-list are filtered by the functions <inline-formula> <tex-math notation="LaTeX">P\left ({{x,y} }\right) </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">W\left ({{x,y} }\right) </tex-math></inline-formula> and the nodes that do not meet the requirements are removed to avoid the generation of irregular paths. Simultaneously, to enhance the stability of the AGV regarding turning paths, the polyline at the turning path is replaced by a cubic B-spline curve. The path planning experimental results applied to different scenarios and different specifications showed that compared with other seven different algorithms, the geometric A-star algorithm reduces the number of nodes by 10% ~ 40%, while the number of turns is reduced by 25%, the turning angle is reduced by 33.3%, and the total distance is reduced by 25.5%. Overall, the simulation results of the path planning confirmed the effectiveness of the geometric A-star algorithm.