论文标题
在线使用移动操纵器机器人的3D探索和检查的次数观看策划师
Online Next-Best-View Planner for 3D-Exploration and Inspection With a Mobile Manipulator Robot
论文作者
论文摘要
可以在不同的情况下部署执行最终用户自主探索的机器人系统，不仅需要映射，而且还需要同时检查最终用户感兴趣的区域。在这项工作中，我们提出了一个新颖的次要视图（NBV）计划者，可以使用移动操纵器机器人对感兴趣的区域进行全面探索和面向用户的探索。我们将探索 - 检验问题作为多目标优化（MOO）的实例，并提出了基于加权的信息增益功能，以计算安装在手臂上的RGB-D摄像机的NBV。对于两种类型的勘探任务，我们将我们的方法与现有的最新探索方法作为基准进行了比较，并证明了我们在映射总量和较低计算要求方面的改进。使用移动操纵器机器人进行的真实实验证明了我们户外方法的实用性和有效性。
Robotic systems performing end-user oriented autonomous exploration can be deployed in different scenarios which not only require mapping but also simultaneous inspection of regions of interest for the end-user. In this work, we propose a novel Next-Best-View (NBV) planner which can perform full exploration and user-oriented exploration with inspection of the regions of interest using a mobile manipulator robot. We address the exploration-inspection problem as an instance of Multi-Objective Optimization (MOO) and propose a weighted-sum-based information gain function for computing NBVs for the RGB-D camera mounted on the arm. For both types of exploration tasks, we compare our approach with an existing state-of-the-art exploration method as the baseline and demonstrate our improvements in terms of total volume mapped and lower computational requirements. The real experiments with a mobile manipulator robot demonstrate the practicability and effectiveness of our approach outdoors.
