论文标题
从物理限制下观察到的集会计划
Assembly Planning from Observations under Physical Constraints
论文作者
论文摘要
本文解决了使用从单个照片中提取的信息和外观的信息复制未知的原语组件的问题。所提出的算法使用物理稳定性约束，凸优化和蒙特卡洛树搜索的简单组合来规划组件，作为由Strips Operators代表的选择和位置操作的序列。在任何真正的机器人系统中不可避免的对象检测中的错误和构成估计的误差，它是有效的，最重要的是鲁棒。通过对UR5操纵器进行彻底的实验，证明了所提出的方法。
This paper addresses the problem of copying an unknown assembly of primitives with known shape and appearance using information extracted from a single photograph by an off-the-shelf procedure for object detection and pose estimation. The proposed algorithm uses a simple combination of physical stability constraints, convex optimization and Monte Carlo tree search to plan assemblies as sequences of pick-and-place operations represented by STRIPS operators. It is efficient and, most importantly, robust to the errors in object detection and pose estimation unavoidable in any real robotic system. The proposed approach is demonstrated with thorough experiments on a UR5 manipulator.
