Thanks to the rapid evolvement of robotic technologies, robot mowing is emerging to liberate humans from the tedious and time-consuming landscape work. Traditionally, robot mowing is perceived as a "Coverage Path Planning" problem, with a simplification that converts non-convex obstacles into convex obstacles. Besides, the converted obstacles are commonly dilated by the robot's circumcircle for collision avoidance. However when applied to robot mowing, an obstacle in a lawn is usually non-convex, imagine a garden on the lawn, such that the mentioned obstacle processing methods would fill in some concave areas so that they are not accessible to the robot anymore and hence produce inescapable uncut areas along the lawn edge, which dulls the landscape's elegance and provokes rework. To shrink the uncut area around the lawn edge we hereby reframe the problem into a brand new problem, named the "Edge Coverage Path Planning" problem that is dedicated to path planning with the objective to cover the edge. Correspondingly, we propose two planning methods, the "big and small disk" and the "sliding chopstick" planning method to tackle the problem by leveraging image morphological processing and computational geometry skills. By validation, our proposed methods can outperform the traditional "dilation-by-circumcircle" method.
翻译:由于机器人技术的迅速发展,机器人修剪正在出现,以将人类从枯燥和耗时的地貌工程中解放出来。传统上,机器人修剪被视为一个“管理道路规划”问题。机械修剪被视为一个“管理道路规划”问题,其简化将非康韦克斯障碍转换成convex障碍。此外,转换障碍通常被机器人环绕环形扩大,以避免碰撞。然而,当应用到机器人修剪时,草坪上的障碍通常是非阴道,想象草坪上的一个花园,从而让上述障碍处理方法填补一些凝固区域,从而使机器人无法再接触这些障碍处理方法,从而在草坪边缘产生无法覆盖的不可切割区域,从而抑制地貌景观的优雅度并引发重新工作。为了将问题缩小到草坪边缘周围的未切割区域,我们在此将问题改造成一个全新的问题,称为“Edge覆盖路径规划”问题,专门用来为覆盖边缘。与此相关的是,我们提议了两种规划方法,即“通过磁盘和小盘处理方法,通过电路面的计算方法, 解决我们的磁盘和计算方法,从而解决我们的磁盘的计算方法”。