LiDAR-Based 3D SLAM for Indoor Mapping

Chan, Teng Hooi; Hesse, Henrik; Ho, Song Guang

doi:10.1109/iccar52225.2021.9463503

Cited by 24 publications

(3 citation statements)

References 9 publications

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“…Exteroceptive sensors acquire information about the environment around the mobile robot, such as images, sound waves, and wireless signals. Examples of exteroceptive sensors include vision sensors [ 20 ], ultrasonic sensors [ 21 ], and LiDAR [ 22 ]. Active sensors send energy to the external environment and then measure the environmental feedback, such as sonar sensors, LIDAR, etc.…”

Section: Introductionmentioning

confidence: 99%

A Review of Sensing Technologies for Indoor Autonomous Mobile Robots

Liu,

Wang,

Xie

et al. 2024

Sensors

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As a fundamental issue in robotics academia and industry, indoor autonomous mobile robots (AMRs) have been extensively studied. For AMRs, it is crucial to obtain information about their working environment and themselves, which can be realized through sensors and the extraction of corresponding information from the measurements of these sensors. The application of sensing technologies can enable mobile robots to perform localization, mapping, target or obstacle recognition, and motion tasks, etc. This paper reviews sensing technologies for autonomous mobile robots in indoor scenes. The benefits and potential problems of using a single sensor in application are analyzed and compared, and the basic principles and popular algorithms used in processing these sensor data are introduced. In addition, some mainstream technologies of multi-sensor fusion are introduced. Finally, this paper discusses the future development trends in the sensing technology for autonomous mobile robots in indoor scenes, as well as the challenges in the practical application environments.

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Section: Introductionmentioning

confidence: 99%

A Review of Sensing Technologies for Indoor Autonomous Mobile Robots

Liu,

Wang,

Xie

et al. 2024

Sensors

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“…In robotic navigation, the maneuvering offset of mobile robots using standalone LiDAR SLAM often struggled to fall below 50 mm even in indoor environments (Chan et al., 2021; Frosi & Matteucci, 2022). RGB‐D SLAM offered an improvement in accuracy, yet maneuvering offset of mobile robots still exceeded about 7 mm (Yang et al., 2020).…”

Section: Introductionmentioning

confidence: 99%

Design and development of robotic collaborative system for automated construction of reciprocal frame structures

Chea,

Bai,

Zhou

2023

Computer aided Civil Eng

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Robotic technologies have shown their potential to improve efficiency, precision, and safety for construction tasks. In this paper, the concept of design for robotic construction (DfRC) is introduced, and robotic collaborative systems are developed for the construction of load‐carrying structures. An automated structural assembly was achieved and demonstrated through robotics with a preference for reciprocal frame (RF) structures. Key innovations include the use of magnetic temporary connections to minimize offsets of mobile robots and linear actuators as temporary supports during construction. Furthermore, specific procedures are formulated to navigate the robots and to target and install the components using a fiducial marker system and simultaneous localization and mapping packages, with consideration of structural deformation during construction due to self‐weight. The successful assembly of a 4.5‐m span RF structure demonstrates the potential of DfRC and the proposed robotic collaborative system in the automated construction of load‐carrying structures.

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“…When 3D reconstruction is done manually using a handheld device, the ability to capture an extensive model of the building is often limited due to physical constraints such as the size of tunnels or large constructions. These issues call for a new and more scalable approach in 3D reconstruction using unmanned aerial vehicles (UAV), optimal scanning methods, and advanced onboard processing algorithms [8,35,45,46].…”

Section: Introductionmentioning

confidence: 99%

Drone-based AI and 3D Reconstruction for Digital Twin Augmentation

Liu²,

Hairul³

et al. 2021

Preprint

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Digital Twin is an emerging technology at the forefront of Industry 4.0, with the ultimate goal of combining the physical space and the virtual space. To date, the Digital Twin concept has been applied in many engineering fields, providing useful insights in the areas of engineering design, manufacturing, automation, and construction industry. While the nexus of various technologies opens up new opportunities with Digital Twin, the technology requires a framework to integrate the different technologies, such as the Building Information Model used in the Building and Construction industry. In this work, an Information Fusion framework is proposed to seamlessly fuse heterogeneous components in a Digital Twin framework from the variety of technologies involved. This study aims to augment Digital Twin in buildings with the use of AI and 3D reconstruction empowered by unmanned aviation vehicles. We proposed a drone-based Digital Twin augmentation framework with reusable and customisable components. A proof of concept is also developed, and extensive evaluation is conducted for 3D reconstruction and applications of AI for defect detection.

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LiDAR-Based 3D SLAM for Indoor Mapping

Cited by 24 publications

References 9 publications

A Review of Sensing Technologies for Indoor Autonomous Mobile Robots

A Review of Sensing Technologies for Indoor Autonomous Mobile Robots

Design and development of robotic collaborative system for automated construction of reciprocal frame structures

Drone-based AI and 3D Reconstruction for Digital Twin Augmentation

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