多机械臂采摘机快速调度与轨迹规划算法，提升采摘效率。
Fast Heuristic Scheduling and Trajectory Planning for Robotic Fruit Harvesters with Multiple Cartesian Arms
- 分区域分配任务，优化机械臂路径与速度
- 12臂时吞吐量随臂数线性提升
- 适合高密度果园的高效自动化采摘
本文提出一种快速启发式算法，用于多笛卡尔坐标系机械臂协同作业的采摘任务调度与轨迹规划。该方法将工作区划分，为各机械臂分配果实采摘序列，确定紧致可行的采摘计划及车辆行驶速度，并生成平滑无碰撞的机械臂运动轨迹。通过合成生成的果实坐标和最多含12个机械臂的采收机设计，评估了算法的采摘吞吐量。结果表明，随着机械臂数量增加，吞吐量单调上升；当果实密度较低时，增加机械臂带来的增益递减，因移动耗时增加；而当果实足够密集时，算法实现与机械臂数量成线性的速度提升。
原文摘要 · Abstract (English)
This work proposes a fast heuristic algorithm for the coupled scheduling and trajectory planning of multiple Cartesian robotic arms harvesting fruits. Our method partitions the workspace, assigns fruit-picking sequences to arms, determines tight and feasible fruit-picking schedules and vehicle travel speed, and generates smooth, collision-free arm trajectories. The fruit-picking throughput achieved by the algorithm was assessed using synthetically generated fruit coordinates and a harvester design featuring up to 12 arms. The throughput increased monotonically as more arms were added. Adding more arms when fruit densities were low resulted in diminishing gains because it took longer to travel from one fruit to another. However, when there were enough fruits, the proposed algorithm achieved a linear speedup as the number of arms increased.
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