FAST-LIVO2: 高效的LiDAR-惯性-视觉传感器融合框架用于实时精准的SLAM任务 本文介绍了一个新型的传感器融合框架——FAST-LIVO2,它结合了LiDAR、惯性测量单元(IMU)和视觉传感器,旨在解决传统单一传感器在SLAM(同步定位与建图)任务中的局限性,特别是在处理复杂环境和提高系统效率方面。FAST-LIVO2通过直接方法进行数据融合...
The focus of this work is to present a novel methodology utilizing the classical SLAM technique and integrating with the swarm agents for localizing, guiding, and retrieving the agents towards the optimal path while using only necessary tracker-based information between the agents. While navigating ...
cslam: contains the Swarm-SLAM nodes; cslam_interfaces: contains the custom ROS 2 messages; cslam_experiments: contains examples of launch files and configurations for different setups; cslam_visualization: contains an online (optional) visualization tool to run on your base station to monitor th...
开源智能无人机SLAM科研集群ROS二次开发ego四旋翼 3183播放 一款微型集群智能无人机是如何诞生的? 2.1万播放 幻思创新FanciSwarm® 无人机全新系列来袭/深度相机D435、Livox激光雷达、英伟达OrinNX、树莓派强效加持!开源无人机/二次开发科研无人机微型 1.0万播放 自研高精度GNSS助力小飞机室外精准翱翔/FanciSwarm...
In this work, we present the concept of swarm SLAM and its constraints, both from a technical and an economical point of view. In particular, we highlight the main challenges of swarm SLAM for gathering, sharing, and retrieving information. We also discuss the strengths and weaknesses of ...
localizationroboticsmappingslamswarm-roboticsmulti-robot-systemsmulti-robot-slamc-slam UpdatedMar 19, 2025 Shell hku-mars/Swarm-LIO2 Star272 Code Issues Pull requests [T-RO 24] Swarm-LIO2: Decentralized, Efficient LiDAR-inertial Odometry for UAV Swarms ...
C. Environmental-Feature-Based Method and Collaborative Simultaneous Localization and Mapping (CSLAM) D. Visual–Inertial–UWB Fusion With Global Consistency III. SYSTEM OVERVIEW A. Notation B. State Estimation Problem of Aerial Swarm C. Global Consistency of the State Estimation ...
(2006). Simultaneous localisation and mapping (SLAM): part I. IEEE Robotics & Automation Magazine, 13(2), 99–110. Article Google Scholar El-Shehawey, M. (2009). On the gambler’s ruin problem for a finite Markov chain. Statistics & Probability Letters, 79(14), 1590–1595. ...
包括双目视觉(stereo camera)传感器,惯性导航模块(IMU),视觉算法计算模块(CVM)三个部分。为无人机的室内定位和避障提供了计算平台和用例。所使用的视觉算法(VIO,SLAM,planner等),提供相对应的开源参考和所作的修改。平台既可以作为无人机视觉定位模块直接使用,也可以作为相关算法开发平台使用。
一、大体总结 首先从AR(Augmented reality 增强现实)切入,讲了SLAM的重要性以及视觉SLAM可以带来的好处,然后以此展开总体的概括了SLAM的发展情况,也分析和介绍了各不同SLAM的性能区别,对各个特性进行了对比和分析,最后总体讲了现有SLAM技术的不足以及对SLAM日后发展的憧憬。 二、知识获取 1.同时定位与地图构建(simultan...