Microdrone-Based Indoor Mapping with Graph SLAM

Review Geography, Physical

UAV in the advent of the twenties: Where we stand and what is next

F. Nex et al.

Summary: This paper reviews best practices for the use of UAVs in remote sensing and mapping applications, emphasizes the need for interdisciplinary research, explores the future trends and impacts of UAVs in photogrammetry and remote sensing.

ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING (2022)

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Article Environmental Sciences

Training a Disaster Victim Detection Network for UAV Search and Rescue Using Harmonious Composite Images

Ning Zhang et al.

Summary: This research focuses on using deep learning to detect victims in disaster debris, proposes a method to generate harmonious composite images for training, and significantly improves detection accuracy.

REMOTE SENSING (2022)

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Proceedings Paper Geography, Physical

MICRO AND MACRO QUADCOPTER DRONES FOR INDOOR MAPPING TO SUPPORT DISASTER MANAGEMENT

S. Karam et al.

Summary: This paper presents the operations and mapping techniques of two drones used for mapping indoor spaces. Both the Crazyflie and MAX drones are capable of mapping cluttered indoor environments and providing sufficient point clouds for quick exploration. The results show that the LIDAR scanner-based system can handle larger office environments with minimal drift, while the Crazyflie drone performs well given its limited sensor configuration.

XXIV ISPRS CONGRESS: IMAGING TODAY, FORESEEING TOMORROW, COMMISSION I (2022)

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Article Remote Sensing

Development of a methodology for real-time retrieving and viewing of spatial data in emergency scenarios

Ahmed Alamouri et al.

Summary: Quick response in emergency situations is crucial, and the development of strategies for emergency management using modern technologies like unmanned aerial vehicles is essential. Providing real-time geo-situation reports to support decision-making in emergencies is complex due to outdated spatial data, leading to the development of a methodology for spatial data management focusing on enabling free access to data in real time. The results show that this methodology can help overcome challenges in spatial data sharing and retrieval, with a focus on performance and time consumption.

APPLIED GEOMATICS (2021)

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Article Geography, Physical

Simple loop closing for continuous 6DOF LIDAR&IMU graph SLAM with planar features for indoor environments

S. Karam et al.

Summary: The article introduces a loop-closing continuous-time LIDAR-IMU SLAM method for indoor environments based on planar features for local and global optimization. The method demonstrates excellent performance in mapping complex indoor environments, with the majority of absolute distances between point clouds generated by the proposed system and a commercial system being less than 3 cm.

ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING (2021)

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Article Environmental Sciences

New Orthophoto Generation Strategies from UAV and Ground Remote Sensing Platforms for High-Throughput Phenotyping

Yi-Chun Lin et al.

Summary: This paper introduces new strategies for generating orthophotos that are conducive to straightforward detection of tassels and panicles in crop phenotyping activities. The strategies focus on improving visual appearance while maintaining geolocation accuracy through smooth digital surface model (DSM) generation and seamline control.

REMOTE SENSING (2021)

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Article Robotics

R 2 LIVE: A Robust, Real-Time, LiDAR-Inertial-Visual Tightly-Coupled State Estimator and Mapping

Jiarong Lin et al.

Summary: The paper introduces a robust multi-sensor fusion framework that can merge measurements from LiDAR, inertial sensor, and visual camera in real-time for accurate state estimation. Extensive experiments show that the proposed framework can improve the accuracy of LiDAR-inertial or visual-inertial odometry.

IEEE ROBOTICS AND AUTOMATION LETTERS (2021)

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Article Engineering, Electrical & Electronic

PFIN: An Efficient Particle Filter-Based Indoor Navigation Framework for UAVs

Gunasekaran Raja et al.

Summary: The paper introduces a Particle Filter-based Indoor Navigation (PFIN) framework for drone navigation, utilizing Quadcopter Mapping Algorithm and Optimized Localization Algorithm to enhance precision and velocity estimation. The efficiency of the algorithms is demonstrated through SITL and HITL simulations, showcasing reduced position error and improved UAV exploration precision.

IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY (2021)

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Article Geography, Physical