We investigate the utility of employing multiple buffers in solving a class of rearrangement problems with pick-n-swap manipulation primitives. In this problem, objects stored randomly in a lattice are to be sorted using a robot arm with k>=1 swap spaces or buffers, capable of holding up to k objects on its end-effector simultaneously. On the structural side, we show that the addition of each new buffer brings diminishing returns in saving the end-effector travel distance while holding the total number of pick-n-swap operations at the minimum. This is due to an interesting recursive cycle structure in random m-permutation, where the largest cycle covers over 60% of objects. On the algorithmic side, we propose fast algorithms for 1D and 2D lattice rearrangement problems that can effectively use multiple buffers to boost solution optimality. Numerical experiments demonstrate the efficiency and scalability of our methods, as well as confirm the diminishing return structure as more buffers are employed.
翻译:我们调查了使用多个缓冲器解决使用轻便吸盘操纵原始件的一类重新排列问题的实用性。 在这个问题中, 随机存储的物体将使用带有 k ⁇ 1 交换空格或缓冲器的机器人臂进行分类, 能够同时在终端效果器上保持 k 对象。 在结构方面, 我们显示, 添加每个新的缓冲器会减少回报率, 以保存最终效果或旅行距离, 并保持最小的拾取- 吸盘操作总数 。 这是因为随机的 m- 移动中, 最大周期覆盖60%以上对象的循环结构很有意思 。 在算法方面, 我们提出了 1D 和 2D 的快速算法 重新配置问题, 能够有效地使用多个缓冲来提升解决方案的优化性。 数字实验显示了我们方法的效率和可缩放性, 并且随着使用更多的缓冲器来确认递减的返回结构 。