计算机工程与应用 ›› 2025, Vol. 61 ›› Issue (20): 123-131.DOI: 10.3778/j.issn.1002-8331.2407-0429

• 路径规划专题 • 上一篇    下一篇

智能土壤采样机改进A*算法路径规划

葛杏卫,苏浩冉,张凯亮,赵月静,秦志英   

  1. 河北科技大学 机械工程学院,石家庄 050000
  • 出版日期:2025-10-15 发布日期:2025-10-15

Improved A* Algorithm Path Planning of Intelligent Soil Sampler

GE Xingwei, SU Haoran, ZHANG Kailiang, ZHAO Yuejing, QIN Zhiying   

  1. School of Mechanical Engineering, Hebei University of Science and Technology, Shijiazhuang 050000, China
  • Online:2025-10-15 Published:2025-10-15

摘要: 智能土壤采样机是一种进行土壤采样作业的高效设备,为了解决未知环境下路径规划的效率和安全性问题,提出了一种改进的A*算法。对估价函数引入动态的权重系数,减少了搜索节点数;将传统的8邻域搜索减少为5邻域搜索,去除了冗余的搜索方向;定义车身半径,进行防碰撞处理,优化了安全性能;采用贝塞尔曲线对路径进行平滑处理。采用农田地块的五点采样法进行仿真实验,结果表明改进A*算法相较于传统A*算法,搜索节点数量平均减少83.66%、搜索时间平均减少56.61%。进一步采用移动机器人在真实环境中进行实验,验证了改进A*算法在实际应用中路径规划的准确率和效率。

关键词: 智能土壤采样机, A*算法, 路径规划, 五点采样法, 动态权重, 贝塞尔曲线平滑

Abstract: Intelligent soil sampler is a kind of efficient equipment for soil sampling. In order to solve the problem of efficiency and safety of path planning in unknown environment, an improved A* algorithm is proposed. Firstly, a dynamic weight coefficient is introduced to the evaluation function to reduce the number of search nodes. Secondly, the traditional 8 neighborhood search is reduced to 5 neighborhood search, and the redundant search direction is removed. Thirdly, the radius of the car body is defined and the anti-collision treatment is carried out to optimize the safety performance. Finally, Bessel curve is used to smooth the path. The simulation results show that compared with the traditional A* algorithm, the improved A* algorithm can reduce the average number of search nodes by 83.66% and the average search time by 56.61%. The accuracy and efficiency of the improved A* algorithm in practical path planning are verified by the experiment of mobile robot in real environment.

Key words: intelligent soil sampling machine, A* algorithm, path planning, five-point sampling method, dynamic weight, Bessel curve smoothing