Calibration of a Multi-Sensor Wheeled Robot for the 3d Mapping of Underground Mining Tunnels

Trybała, Paweł; Szrek, Jarosław; Remondino, Fabio; Wodecki, Jacek; Zimroz, Radosław

doi:10.5194/isprs-archives-xlviii-2-w2-2022-135-2022

Cited by 5 publications

(2 citation statements)

References 31 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…As a constituent of the Intel RealSense suite of depth cameras, it leverages a synthesis of infrared sensors and camera technology to capture depth data. Moreover, the RealSense software package 30 encompasses a calibration utility, enabling enhanced precision in the calibration process and the extraction of intrinsic camera parameters, inclusive of distortion coefficients.…”

Section: Results Of Numerical Experimentsmentioning

confidence: 99%

Neural network-based algorithm for door handle recognition using RGBD cameras

Mochurad,

Hladun

2024

Sci Rep

View full text Add to dashboard Cite

The ability to recognize and interact with a variety of doorknob designs is an important component on the path to true robot adaptability, allowing robotic systems to effectively interact with a variety of environments and objects The problem addressed in this paper is to develop and implement a method for recognizing the position of a door handle by a robot using data from an RGBD camera. To achieve this goal, we propose a revolutionary approach designed for autonomous robots that allows them to identify and manipulate door handles in different environments using data obtained from RGBD cameras. This was achieved by creating and annotating a complete dataset consisting of 5000 images of door handles from different angles, with the coordinates of the vertices of the bounding rectangles labeled. The architectural basis of the proposed approach is based on MobileNetV2, combined with a special decoder that optimally increases the resolution to 448 pixels. A new activation function specially designed for this neural network is implemented to ensure increased accuracy and efficiency of raw data processing. The most important achievement of this study is the model's ability to work in real-time, processing up to 16 images per second. This research paves the way for new advancements in the fields of robotics and computer vision, making a substantial contribution to the practical deployment of autonomous robots in a myriad of life's spheres.

show abstract

Section: Results Of Numerical Experimentsmentioning

confidence: 99%

Neural network-based algorithm for door handle recognition using RGBD cameras

Mochurad,

Hladun

2024

Sci Rep

View full text Add to dashboard Cite

show abstract

“…Among the various application areas, the digitisation of built heritage presents specific needs, including: (i) the need to document small features within large volumes, (ii) complex and inaccessible spaces, (iii) variety of materials, (iv) lighting conditions that cannot be controlled, and (v) the need to process large amounts of data (Argyridou et al, 2023). Many papers have compared portable mobile mapping systems (PMMS) each other or with static terrestrial laser scanner (TLS) in various scenarios (Nocerino et al 2017, Tucci et al, 2018, Ulvi & Yiğit, 2022, Tanduo et al 2023, Trybała et al, 2023. This article aims to compare the results of surveys done with a static TLS and a PMMS and to validate their suitability for the documentation of the built heritage (Sammartano & Spanò, 2018).…”

Section: Introductionmentioning

confidence: 99%

A Comparison Between Terrestrial Laser Scanning and Hand-Held Mobile Mapping for the Documentation of Built Heritage

Conti,

Pagliaricci,

Bonora

et al. 2024

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

View full text Add to dashboard Cite

Abstract. The increasing demand for 3D digital models has spurred the rapid evolution of technologies to acquire, process, and disseminate 3D data of physical artifacts. Current scanners meet building surveying needs, prompting the exploration of closed systems with multiple sensors, custom accessories, control systems, and varied data processing approaches. While efficient in specific conditions, these systems require careful consideration of factors like technical requirements, environmental conditions, and the intended use of the final model. This article compares a static terrestrial laser scanner (TLS) and a portable mobile mapping system (PMMS) for documenting built heritage, focusing on the City Hall of Montecatini Terme in Italy. The Leica Geosystems RTC360 scanner provides quick scanning times and pre-alignment during fieldwork, reducing post-processing efforts. The Leica BLK2GO, belonging to the PMMS family, utilizes laser SLAM, visual SLAM, and inertial IMU measurements for rapid large-area documentation. The comparison assesses accuracy, completeness, and detail recognition, revealing that both systems are suitable for heritage documentation requiring centimetre-level accuracy. However, differences in point density and roughness indicate that the RTC360 may be better for intricate details. The BLK2GO excels in efficiency but is more oriented toward general representations at the architectural scale. This study emphasizes the importance of evaluating different methodologies based on project objectives and desired levels of detail, providing insights into the strengths and limitations of each system for diverse applications in heritage documentation.

show abstract

MIN3D Dataset: MultI-seNsor 3D Mapping with an Unmanned Ground Vehicle

Trybała,

Szrek,

Remondino

et al. 2023

PFG

View full text Add to dashboard Cite

The research potential in the field of mobile mapping technologies is often hindered by several constraints. These include the need for costly hardware to collect data, limited access to target sites with specific environmental conditions or the collection of ground truth data for a quantitative evaluation of the developed solutions. To address these challenges, the research community has often prepared open datasets suitable for developments and testing. However, the availability of datasets that encompass truly demanding mixed indoor–outdoor and subterranean conditions, acquired with diverse but synchronized sensors, is currently limited. To alleviate this issue, we propose the MIN3D dataset (MultI-seNsor 3D mapping with an unmanned ground vehicle for mining applications) which includes data gathered using a wheeled mobile robot in two distinct locations: (i) textureless dark corridors and outside parts of a university campus and (ii) tunnels of an underground WW2 site in Walim (Poland). MIN3D comprises around 150 GB of raw data, including images captured by multiple co-calibrated monocular, stereo and thermal cameras, two LiDAR sensors and three inertial measurement units. Reliable ground truth (GT) point clouds were collected using a survey-grade terrestrial laser scanner. By openly sharing this dataset, we aim to support the efforts of the scientific community in developing robust methods for navigation and mapping in challenging underground conditions. In the paper, we describe the collected data and provide an initial accuracy assessment of some visual- and LiDAR-based simultaneous localization and mapping (SLAM) algorithms for selected sequences. Encountered problems, open research questions and areas that could benefit from utilizing our dataset are discussed. Data are available at https://3dom.fbk.eu/benchmarks.

show abstract

Calibration of a Multi-Sensor Wheeled Robot for the 3d Mapping of Underground Mining Tunnels

Cited by 5 publications

References 31 publications

Neural network-based algorithm for door handle recognition using RGBD cameras

Neural network-based algorithm for door handle recognition using RGBD cameras

A Comparison Between Terrestrial Laser Scanning and Hand-Held Mobile Mapping for the Documentation of Built Heritage

MIN3D Dataset: MultI-seNsor 3D Mapping with an Unmanned Ground Vehicle

Contact Info

Product

Resources

About