论文标题

在线本地化和机器人探索任务中3D视觉反馈的彩色网格重建体系结构

Online Localisation and Colored Mesh Reconstruction Architecture for 3D Visual Feedback in Robotic Exploration Missions

论文作者

Serdel, Quentin, Grand, Christophe, Marzat, Julien, Moras, Julien

论文摘要

本文介绍了用于地面探索机器人的在线本地化和彩色网状重建(OLCMR)ROS感知体系结构,旨在在具有挑战性的未知环境中执行强大的同时定位和映射(SLAM),并实时提供相关的彩色3D网格表示。它旨在被远程人类操作员使用,以轻松在任务期间或之后可视化映射的环境,或作为在勘探机器人技术领域进行进一步研究的开发基础。该体系结构主要由精心挑选的基于激光雷达的SLAM算法的开源ROS实现以及使用点云和RGB摄像机图像投影到3D空间中的彩色表面重建过程。在较新的大学手持式LIDAR-VISION参考数据集上评估了整体表演,并在分别在城市和乡村户外环境中分别在代表性轮式机器人上收集的实验轨迹。索引术语:现场机器人,映射,猛击,彩色表面重建

This paper introduces an Online Localisation and Colored Mesh Reconstruction (OLCMR) ROS perception architecture for ground exploration robots aiming to perform robust Simultaneous Localisation And Mapping (SLAM) in challenging unknown environments and provide an associated colored 3D mesh representation in real time. It is intended to be used by a remote human operator to easily visualise the mapped environment during or after the mission or as a development base for further researches in the field of exploration robotics. The architecture is mainly composed of carefully-selected open-source ROS implementations of a LiDAR-based SLAM algorithm alongside a colored surface reconstruction procedure using a point cloud and RGB camera images projected into the 3D space. The overall performances are evaluated on the Newer College handheld LiDAR-Vision reference dataset and on two experimental trajectories gathered on board of representative wheeled robots in respectively urban and countryside outdoor environments. Index Terms: Field Robots, Mapping, SLAM, Colored Surface Reconstruction

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