A novel motion planning algorithm for robotic bush trimming is presented. The algorithm is based on an optimal route search over a graph. Differently from other works in robotic surface coverage, it entails both accuracy in the surface sweeping task and smoothness in the motion of the robot arm. The proposed method requires the selection of a custom objective function in the joint space for optimal node traversal scheduling, as well as a kinematically constrained time interpolation. The algorithm was tested in simulation using a model of the Jaco arm and three target bush shapes. Analysis of the simulated motions showed how, differently from classical coverage techniques, the proposed algorithm is able to ensure high tool positioning accuracy while avoiding excessive arm motion jerkiness. It was reported that forbidding manipulation posture changes during the cutting phase of the motion is a key element for task accuracy, leading to a decrease of the tool positioning error up to 90%. Furthermore, the algorithm was validated in a real-world trimming scenario with boxwood bushes. A target of 20 mm accuracy was proposed for a trimming result to be considered successful. Results showed that on average 82% of the bush surface was affected by trimming, and 51% of the trimmed surface was cut within the desired level of accuracy. Despite the fact that the trimming accuracy turned out to be lower than the stated requirements, it was found out this was mainly a consequence of the inaccurate, early stage vision system employed to compute the target trimming surface. By contrast, the trimming motion planning algorithm generated trajectories that smoothly followed their input target and allowed effective branch cutting.

中文翻译：

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灌木修剪机器人手臂的覆盖轨迹规划

提出了一种用于机器人灌木修剪的新运动规划算法。该算法基于对图形的最佳路径搜索。与机器人表面覆盖方面的其他工作不同，它需要表面清扫任务的准确性和机器人手臂运动的平滑度。所提出的方法需要在联合空间中选择一个自定义目标函数来优化节点遍历调度，以及一个运动学约束的时间插值。使用 Jaco 臂和三个目标灌木形状的模型在仿真中测试了该算法。模拟运动的分析表明，与经典的覆盖技术不同，所提出的算法如何能够确保高工具定位精度，同时避免过度的手臂运动急动。据报道，在运动的切削阶段禁止操纵姿势变化是确保任务精度的关键因素，可将刀具定位误差降低高达 90%。此外，该算法在具有黄杨木灌木的真实修剪场景中得到了验证。提出了 20 毫米精度的目标，以使修剪结果被认为是成功的。结果表明，平均 82% 的衬套表面受到修剪的影响，51% 的修剪表面在所需的精度水平内被切割。尽管事实证明修剪精度低于规定的要求，但发现这主要是用于计算目标修剪表面的早期视觉系统不准确的结果。相比之下，