提出一种高效方法，精准估计立方体物体姿态并实时纠正误差。
An Efficient Method for Accurate Pose Estimation and Error Correction of Cuboidal Objects
- 用线性时间算法替代传统局部注册，提升姿态估计速度
- 在保持高精度的前提下，显著降低姿态误差
- 适合需要快速精准抓取的机器人场景
本文提出一种高效方法，用于精确估计立方体形状物体的姿态，旨在以时间高效的方式减少目标姿态误差。典型的姿态估计方法如全局点云配准容易产生微小姿态偏差，通常需借助局部注册算法提升精度。然而，局部注册存在执行时间开销大、最终姿态误差不确定性高的问题。为此，本文提出一种替代方案，采用线性时间方法实现姿态误差估计与校正。论文首先概述整体解决方案，随后详细描述所提算法的各个模块。
原文摘要 · Abstract (English)
The proposed system outlined in this paper is a solution to a use case that requires the autonomous picking of cuboidal objects from an organized or unorganized pile with high precision. This paper presents an efficient method for precise pose estimation of cuboid-shaped objects, which aims to reduce errors in target pose in a time-efficient manner. Typical pose estimation methods like global point cloud registrations are prone to minor pose errors for which local registration algorithms are generally used to improve pose accuracy. However, due to the execution time overhead and uncertainty in the error of the final achieved pose, an alternate, linear time approach is proposed for pose error estimation and correction. This paper presents an overview of the solution followed by a detailed description of individual modules of the proposed algorithm.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。