Computer Engineering and Applications ›› 2024, Vol. 60 ›› Issue (16): 325-332.DOI: 10.3778/j.issn.1002-8331.2306-0002

• Engineering and Applications • Previous Articles    

Path Planning Study of Mobile Spraying Robot in Tomato Greenhouse

GAO Xingwang, REN Lisheng, WANG Fang   

  1. 1.College of Information Science and Technology, Hebei Agricultural University, Baoding, Hebei 071001, China
    2.Hebei Key Laboratory of Agricultural Big Data, Baoding, Hebei 071001, China
  • Online:2024-08-15 Published:2024-08-15

番茄温室内移动喷药机器人的路径规划研究

高兴旺,任力生,王芳   

  1. 1.河北农业大学 信息科学与技术学院,河北 保定 071001
    2.河北省农业大数据重点实验室,河北 保定 071001

Abstract: When the mobile spraying robot operates in the tomato greenhouse, there are problems such as low planning path efficiency, poor smoothness, and potential safety hazards in the path. A path planning algorithm for tomato greenhouse mobile spraying robot with optimized A* algorithm and DWA algorithm is proposed. Fully consider the specific environment of the tomato greenhouse, define the safety distance of the operation, and expand the planting area to ensure the safe operation of the mobile spraying robot. By adding dynamic weight factors to the heuristic function, key node extraction is used to improve the efficiency of global path planning, and turning points and three B-spline curves are introduced to ensure the comprehensive coverage and smoothness of the path. Finally, the DWA algorithm is integrated to ensure that the mobile spraying robot avoids the sudden obstacles. The experimental results show that the optimized algorithm is safer and smoother than the path planned by the traditional algorithm, the coverage area is complete, the planning efficiency is significantly improved, and the fusion algorithm successfully avoids the sudden obstacles in the path. This proposed scheme meets the working requirements of mobile spraying robots in complex tomato greenhouses.

Key words: tomato greenhouse, mobile spraying robot, path planning, A* algorithm, dynamic window approach (DWA)

摘要: 移动喷药机器人在番茄温室内作业时,存在规划路径效率低、平滑性差以及路径存在安全隐患等问题。提出了一种优化A*算法融合DWA算法的番茄温室移动喷药机器人的路径规划算法。充分考虑番茄温室具体环境,定义作业安全距离及对种植区进行膨胀化处理,保证移动喷药机器人安全作业;通过为启发函数添加动态权重因子,采用关键节点提取技术提高全局路径规划效率,同时引入转弯点以及三次B样条曲线确保路径的全面覆盖及平滑性;最后融合DWA算法保证移动喷药机器人对突现障碍物的躲避。使用Matlab构建番茄温室环境进行仿真验证,实验结果表明,优化后的算法比传统算法规划出的路径更安全、平滑,覆盖喷药区域完整,规划效率明显提升,融合算法成功实现了对路径突现障碍物的躲避。该方案满足移动喷药机器人在复杂番茄温室中的作业需求。

关键词: 番茄温室, 移动喷药机器人, 路径规划, A*算法, 动态窗口法(DWA)