An Improved A-Star Algorithm for Global Path Planning of Unmanned Surface Vehicle

Wang, Yifan; Geng, Qingbo; Fei, Qing; Wang, Bo; Zhao, Di

doi:10.23919/ccc58697.2023.10239747

Cited by 2 publications

(1 citation statement)

References 17 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…To address the issue of a high number of search nodes and redundant nodes in the generating path, Haoxin Liu et al [ 7 ] improved the evaluation function of the A-star algorithm and successfully reduced the number of search nodes. Yifan Wang et al [ 8 ] designed a redundancy evaluation function and used an adaptive variable step size strategy to reduce the number of expansion nodes, successfully eliminating redundant nodes in the path. Jing Zhang et al [ 9 ] improved the evaluation function of the A-star algorithm and combined it with the artificial potential field method to effectively reduce the number of redundant nodes in the path.…”

Section: Introductionmentioning

confidence: 99%

An Improved A-Star Path Planning Algorithm Based on Mobile Robots in Medical Testing Laboratories

Yin,

Tan,

Wang

et al. 2024

Sensors

View full text Add to dashboard Cite

In the blood sample management pipeline environment, we have innovatively improved the traditional A-star algorithm to enhance the efficiency of mobile robots. This study employs a grid environmental modeling approach to accurately simulate medical testing laboratories. On the grid map, we utilize an 8-neighbor search method for path planning to accommodate the complex structure within the laboratory. By introducing an improved evaluation function and a bidirectional search strategy, we have successfully reduced the number of search nodes and significantly improved path search efficiency. Additionally, we eliminate redundant nodes in the path, smooth the path using cubic uniform B-spline curves, remove unnecessary inflection points, and further optimize the motion trajectory of the robot. The experimental results of the path planning simulation under different scenarios and specifications show that the improved A-star algorithm has higher search efficiency and traverses fewer nodes compared to the traditional A-star algorithm and the bidirectional A-star algorithm. Overall, the simulation experiments verify the feasibility of the improved A-star algorithm, which can better meet the needs of actual mobile robots in real medical testing laboratories.

show abstract

Section: Introductionmentioning

confidence: 99%