双螺旋驱动式机器人全覆盖作业路径规划算法研究

Full-coverage Path Planning Algorithm for Dual-helix Driven Robot in Convex Polygonal Farmlands

摘要:

针对复杂农田环境下农业机器人在自主导航与作业路径规划方面的核心需求，特别是在不规则田块与软黏稻田场景中常见的路径覆盖率低、转弯冗余高以及路径连续性差等问题，本文提出一种面向多边形边界田块、适用于双螺旋驱动式农田机器人的全覆盖路径规划算法。该算法充分融合田块几何特征与机器人运动学约束，首先将作业区域划分为中心平行作业区与外围轮廓平行作业区，分别对应中心条带遍历路径与轮廓平行条带遍历路径。进一步将路径细分为作业路径与非作业路径，后者包括中心区域衔接路径、区域衔接路径、轮廓平行区域衔接路径以及进出田块路径等部分。本文阐述了各部分路径的生成原理，通过“长边作业”确定中心区域的最优作业方向，结合Warnsdorff规则优化条带遍历顺序，并引入Dubins路径与Reeds-Shepp路径模型，提升路径在转向过程中的连续性和可执行性。综合考虑作业路径长度、算法计算耗时与作业覆盖率等性能指标，选用双螺旋驱动式机器人作为平台载体，分别在矩形、梯形、不规则四边形、不规则多边形4类典型田块进行了仿真与实地对比测试。试验结果表明，本文算法在4种典型田块田间作业中可实现96.69%~97.80%的覆盖率，路径重叠率控制在1.77%~2.30%之间，路径整体连续、无越界转弯，表现出良好的执行稳定性与环境适应性。研究结果为复杂环境下农田作业机器人提供了高鲁棒性、高适应性的路径规划方案，具备良好的工程可行性与推广价值。

Abstract:

Aiming to address the core challenges faced by agricultural robots in autonomous navigation and path planning under complex farmland environments—particularly in irregular plots and soft, sticky paddy fields where common issues included low coverage rate, excessive turning redundancy, and poor path continuity, a full-coverage path planning algorithm tailored for convex polygonal farmlands and compatible with dual-helix driven agricultural robots was proposed. The algorithm integrated both the geometric characteristics of the farmland and the kinematic constraints of the robot. The working area was initially divided into a central parallel-working zone and a peripheral contour-following zone, corresponding respectively to strip-based traversal paths and boundary-parallel strip traversal paths. The complete path was further segmented into working and non-working paths, including center-region connection paths, inter-region transitions, contour-parallel region transitions, and entry/exit paths. The methodology for generating each type of path was detailed. An optimal working direction was determined via the “long-side-first” principle for the central region, and the Warnsdorff rule was applied to optimize the sequence of strip traversal. Dubins and Reeds-Shepp path models were introduced to enhance continuity and feasibility during turns. Considering metrics such as path length, computation time, and coverage rate, the algorithm was implemented on a dual-helix driven robot and tested in simulations and field experiments across four typical farmland types: rectangular, trapezoidal, irregular quadrilateral, and irregular polygonal plots. Experimental results demonstrated that the proposed algorithm achieved a coverage rate between 96.69% and 97.80%, with a path overlap rate controlled within 1.77%~2.30%. The generated paths were continuous and boundary-safe, indicating strong execution stability and environmental adaptability. The research result can provide a robust and adaptable path planning solution for agricultural robots operating in complex environments, with promising engineering feasibility and application potential.