Browsing by Author "Chen, Yuwei"
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- The accuracy comparison of three simultaneous localization and mapping (SLAM)-based indoor mapping technologies
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä(2018-10-01) Chen, Yuwei; Tang, Jian; Jiang, Changhui; Zhu, Lingli; Lehtomäki, Matti; Kaartinen, Harri; Kaijaluoto, Risto; Wang, Yiwu; Hyyppä, Juha; Hyyppä, Hannu; Zhou, Hui; Pei, Ling; Chen, RuizhiThe growing interest and the market for indoor Location Based Service (LBS) have been drivers for a huge demand for building data and reconstructing and updating of indoor maps in recent years. The traditional static surveying and mapping methods can’t meet the requirements for accuracy, efficiency and productivity in a complicated indoor environment. Utilizing a Simultaneous Localization and Mapping (SLAM)-based mapping system with ranging and/or camera sensors providing point cloud data for the maps is an auspicious alternative to solve such challenges. There are various kinds of implementations with different sensors, for instance LiDAR, depth cameras, event cameras, etc. Due to the different budgets, the hardware investments and the accuracy requirements of indoor maps are diverse. However, limited studies on evaluation of these mapping systems are available to offer a guideline of appropriate hardware selection. In this paper we try to characterize them and provide some extensive references for SLAM or mapping system selection for different applications. Two different indoor scenes (a L shaped corridor and an open style library) were selected to review and compare three different mapping systems, namely: (1) a commercial Matterport system equipped with depth cameras; (2) SLAMMER: a high accuracy small footprint LiDAR with a fusion of hector-slam and graph-slam approaches; and (3) NAVIS: a low-cost large footprint LiDAR with Improved Maximum Likelihood Estimation (IMLE) algorithm developed by the Finnish Geospatial Research Institute (FGI). Firstly, an L shaped corridor (2nd floor of FGI) with approximately 80 m length was selected as the testing field for Matterport testing. Due to the lack of quantitative evaluation of Matterport indoor mapping performance, we attempted to characterize the pros and cons of the system by carrying out six field tests with different settings. The results showed that the mapping trajectory would influence the final mapping results and therefore, there was optimal Matterport configuration for better indoor mapping results. Secondly, a medium-size indoor environment (the FGI open library) was selected for evaluation of the mapping accuracy of these three indoor mapping technologies: SLAMMER, NAVIS and Matterport. Indoor referenced maps were collected with a small footprint Terrestrial Laser Scanner (TLS) and using spherical registration targets. The 2D indoor maps generated by these three mapping technologies were assessed by comparing them with the reference 2D map for accuracy evaluation; two feature selection methods were also utilized for the evaluation: interactive selection and minimum bounding rectangles (MBRs) selection. The mapping RMS errors of SLAMMER, NAVIS and Matterport were 2.0 cm, 3.9 cm and 4.4 cm, respectively, for the interactively selected features, and the corresponding values using MBR features were 1.7 cm, 3.2 cm and 4.7 cm. The corresponding detection rates for the feature points were 100%, 98.9%, 92.3% for the interactive selected features and 100%, 97.3% and 94.7% for the automated processing. The results indicated that the accuracy of all the evaluated systems could generate indoor map at centimeter-level, but also variation of the density and quality of collected point clouds determined the applicability of a system into a specific LBS. - Calibration and Signal Processing of Airborne Stand Profile Radar used in forest inventory
Sähkötekniikan korkeakoulu | Master's thesis(2016-08-24) Feng, ZiyiTomoRadar is a helicopter/UAV (Unmanned Aerial Vehicle) based FM-CW microwave ranging radar designed for the forest inventory. Developed by FGI (Finnish Geospatial Research Institute), TomoRadar can scan forest with Ku-band signals and then receive the backscatter signal from targets. The target distance can be figured out from the backscattered signal. Furthermore, various information around forest can be evaluated. As a ranging scatterometer the system calibration and signal processing are necessary and critical tasks. In This thesis, these two major problems are researched and solved. The system calibration is limited to complete on ground and restricted in a particular range despite TomoRadar works on helicopter. Thus the range calibration experiment is conducted on the ground test field with a Luneburg lens. Besides, power calibration of system backscatter signal is researched through electrical component tests. The linearity of the radar system frequency sweep is critical in FM-CW radars. Hence, it is studied in this thesis. When TomoRadar works, the output of the whole system is analog signal in intimidate frequency (IF) band. A digitizer samples and records the output analog signal. With these signal, the information around forest cannot be obtained. To draw stand profile of forest and research forest information, the IF band signals need to be further processed. This is signal processing part of the thesis work. As a result of this thesis work, TomoRadar range calibration was achieved. The calibration results were verified by the helicopter based flying tests. The results present that the calibration completed on ground test field applied with the situation that TomoRadar works in air and scans targets in long distance. The linearity of system frequency sweep generated by DDS (Direct Digital Synthesizer) is verified. Finally, the test forest backscattered data was processed and the ranges were evaluated. Some targets stand profiles are generated and presented in this thesis - Environment Awareness with Hyperspectral LiDAR Technologies
School of Science | Doctoral dissertation (article-based)(2020) Chen, YuweiLiDAR (Light Detection And Ranging, also known as LADAR) is an active optical remote sensing technique that can measure the distance by counting the time of flight (ToF) of the transmitted laser and acquire other physical properties of a target by illuminating the target with a light source, often using a pulsed laser due to the high spatial and temporal coherence nature. Traditionally a monochromatic laser beam can map physical features with a very high spatial resolution in a non-contact manner. Limited by the employed monochromatic laser source, traditional LiDAR sensors usually operate at one or several discrete wavelength bands. These systems can provide high-accuracy spatial information, but restricted spectral information: compared with a passive spectrometer, the spectral information and spectral resolution are inadequate for some particular remote sensing applications. The motivation of this research is straightforward: investigating SCL-based hyperspectral LiDAR (HSL) technology, more specifically: investigating HSL technique with different system configuration, confirming their accuracy both in spatial and spectral measurements, and conducting various feasibility studies towards environmental awareness applications, more specific, in in forestry, plant science and mining. The emphasis was on system development and methodology development. The specific aims of this dissertation based on six prototyped hyperspectral LiDAR were as follows: • to investigate different hardware techniques including optics, electronics, and post-processing techniques for HSL system development covering the spectrum from visible to near-infrared (VNIR) to shortwave infrared (SWIR) (for better eye-safety operation) with discrete or continuous spectral channels for remote sensing applications; • to develop methods to evaluate the performance of the HSL systems concerning the spectral measurement accuracy, the range stability and resolution over the covered spectral range ; • to assess the feasibility of the developed methods in forestry, mining and plant sciences related environment awareness applications with the point clouds or range measurement containing the spectral information. - Fast Fingerprint Database Maintenance for Indoor Positioning Based on UGV SLAM
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä(2015) Tang, Jian; Chen, Yuwei; Chen, Liang; Liu, Jinbing; Hyyppä, Juha; Kukko, Antero; Kaartinen, Harri; Hyyppä, Hannu; Chen, Ruizhi - Feasibility Study of Using Mobile Laser Scanning Point Cloud Data for GNSS Line of Sight Analysis
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä(2017) Chen, Yuwei; Zhu, Lingli; Tang, Jian; Pei, Ling; Kukko, Antero; Wang, Yiwu; Hyyppä, Juha; Hyyppä, HannuThe positioning accuracy with good GNSS observation can easily reach centimetre level, supported by advanced GNSS technologies. However, it is still a challenge to offer a robust GNSS based positioning solution in a GNSS degraded area. The concept of GNSS shadow matching has been proposed to enhance the GNSS based position accuracy in city canyons, where the nearby high buildings block parts of the GNSS radio frequency (RF) signals. However, the results rely on the accuracy of the utilized ready-made 3D city model. In this paper, we investigate a solution to generate a GNSS shadow mask with mobile laser scanning (MLS) cloud data. The solution includes removal of noise points, determining the object which only attenuated the RF signal and extraction of the highest obstruction point, and eventually angle calculation for the GNSS shadow mask generation. By analysing the data with the proposed methodology, it is concluded that the MLS point cloud data can be used to extract the GNSS shadow mask after several steps of processing to filter out the hanging objects and the plantings without generating the accurate 3D model, which depicts the boundary of GNSS signal coverage more precisely in city canyon environments compared to traditional 3D models. - Instance-Aware Semantic Segmentation of Road Furniture in Mobile Laser Scanning Data
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä(2022-10-01) Li, Fashuai; Zhou, Zhize; Xiao, Jianhua; Chen, Ruizhi; Lehtomäki, Matti; Elberink, Sander Oude; Vosselman, George; Hyyppä, Juha; Chen, Yuwei; Kukko, AnteroIn this paper, we present an improved framework for the instance-aware semantic segmentation of road furniture in mobile laser scanning data. In our framework, we first detect road furniture from mobile laser scanning point clouds. Then we decompose the detected pieces of road furniture into poles and their attached components, and extract the instance information of the components with different features. Most importantly, we classify the components into different categories by combining a classifier and a probabilistic graphic model named DenseCRF, which is the major contribution of this paper. For the classification of the components using DenseCRF, the unary potentials and the pairwise potentials are first obtained. The unary potentials are obtained from the classifier which takes the instance information of components as the input. The pairwise potentials are calculated considering contextual relations between components. By utilising DenseCRF, the contextual consistency of components is preserved, and the performance is significantly improved compared to our previous work. We collect three datasets to test our framework, and compare the classification performances of six different classifiers with and without DenseCRF. The combination of random forest with DenseCRF outperforms the other methods and achieves high overall accuracies of 83.7%, 96.4% and 95.3% in these three datasets. Experimental results demonstrate that our framework reliably assigns both semantic information and instance information for mobile laser scanning point clouds of road furniture. - Mid-long wavelength infrared absorptance of hyperdoped silicon via femtosecond laser microstructuring
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä(2022-01-17) Sun, Haibin; Liu, Xiaolong; Zhao, Li; Jia, Jianxin; Jiang, Changhui; Xiao, Jiamin; Chen, Yuwei; Xu, Long; Duan, Zhiyong; Rao, Peng; Sun, ShengliHyperdoped silicon (hSi) fabricated via femtosecond laser irradiation has emerged as a promising photoelectric material with strong broadband infrared (IR) absorption. In this work, we measured the optical absorptance of the hSi in the wavelength of 0.3–16.7 µm. Unlike the near to mid wavelength IR absorption, the mid-long wavelength IR (M–LWIR) absorption is heavily dependent on the surface morphology and the dopants. Furthermore, calculations based on coherent potential approximation (CPA) reveal the origin of free carrier absorption, which plays an important role in the M–LWIR absorption. As a result, a more comprehensive picture of the IR absorption mechanism is drawn for the optoelectronic applications of the hSi. - Miniaturizing Hyperspectral Lidar System Employing Integrated Optical Filters
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä(2024-05) Sun, Haibin; Wang, Yicheng; Sun, Zhipei; Wang, Shaowei; Sun, Shengli; Jia, Jianxin; Jiang, Changhui; Hu, Peilun; Yang, Haima; Yang, Xing; Karjalnen, Mika; Hyyppä, Juha; Chen, YuweiHyperspectral LiDAR (HSL) has been utilized as an efficacious technique in object classification and recognition based on its unique capability to obtain ranges and spectra synchronously. Different kinds of HSL prototypes with varied structures have been promoted and measured its performance. However, almost all of these HSL prototypes employ complex and large spectroscopic devices, such as an Acousto-Optic Tunable Filter and Liquid-Crystal Tunable Filter, which makes this HSL system bulky and expensive, and then hinders its extensive application in many fields. In this paper, a smart and smaller spectroscopic component, an intergraded optical filter (IOF), is promoted to miniaturize these HSL systems. The system calibration, range precision, and spectral profile experiments were carried out to test the HSL prototype. Although the IOF employed here only covered a wavelength range of 699–758 nm with a six-channel passband and showed a transmittance of less than 50%, the HSL prototype showed excellent performance in ranging and spectral profile collecting. The spectral profiles collected are well in accordance with those acquired based on the AOTF. The spectral profiles of the pizza, vegetables, plants, and ore samples collected by the HSL based on an IOF can effectively reveal the status of the plants, the component materials, and ore species. Finally, we also showed the integrated design of the HSL based on a three-dimensional IOF and combined with a detector. The performance and designs of this HSL system based on an IOF show great potential for miniaturizing in some specific applications. - A practical method utilizing multi-spectral LiDAR to aid points cloud matching in SLAM
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä(2020) Jiang, Changhui; Chen, Yuwei; Tian, Wenxin; Feng, Ziyi; Li, Wei; Zhou, Chunchen; Shao, Hui; Puttonen, Eetu; Hyyppa, JuhaLight Detection and Ranging (LiDAR) sensors are popular in Simultaneous Localization and Mapping (SLAM) owing to their capability of obtaining ranging information actively. Researchers have attempted to use the intensity information that accompanies each range measurement to enhance LiDAR SLAM positioning accuracy. However, before employing LiDAR intensities in SLAM, a calibration operation is usually carried out so that the intensity is independent of the incident angle and range. The range is determined from the laser beam transmitting time. Therefore, the key to using LiDAR intensities in SLAM is to obtain the incident angle between the laser beam and target surface. In a complex environment, it is difficult to obtain the incident angle robustly. This procedure also complicates the data processing in SLAM and as a result, further application of the LiDAR intensity in SLAM is hampered. Motivated by this problem, in the present study, we propose a Hyperspectral LiDAR (HSL)-based-intensity calibration-free method to aid point cloud matching in SLAM. HSL employed in this study can obtain an eight-channel range accompanied by corresponding intensity measurements. Owing to the design of the laser, the eight-channel range and intensity were collected with the same incident angle and range. According to the laser beam radiation model, the ratio values between two randomly selected channels' intensities at an identical target are independent of the range information and incident angle. To test the proposed method, the HSL was employed to scan a wall with different coloured papers pasted on it (white, red, yellow, pink, and green) at four distinct positions along a corridor (with an interval of 60 cm in between two consecutive positions). Then, a ratio value vector was constructed for each scan. The ratio value vectors between consecutive laser scans were employed to match the point cloud. A classic Iterative Closest Point (ICP) algorithm was employed to estimate the HSL motion using the range information from the matched point clouds. According to the test results, we found that pink and green papers were distinctive at 650, 690, and 720 nm. A ratio value vector was constructed using 650-nm spectral information against the reference channel. Furthermore, compared with the classic ICP using range information only, the proposed method that matched ratio value vectors presented an improved performance in heading angle estimation. For the best case in the field test, the proposed method enhanced the heading angle estimation by 72%, and showed an average 25.5% improvement in a featureless spatial testing environment. The results of the primary test indicated that the proposed method has the potential to aid point cloud matching in typical SLAM of real scenarios. - SLAM-Aided Stem Mapping for Forest Inventory with Small-Footprint Mobile LiDAR
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä(2015) Tang, Jian; Chen, Yuwei; Kukko, Antero; Kaartinen, Harri; Jaakkola, Anttoni; Khoramshahi, Ehsan; Hakala, Teemu; Hyyppä, Juha; Holopainen, Markus; Hyyppä, Hannu - Stochastic cluster embedding
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä(2023-02) Yang, Zhirong; Chen, Yuwei; Sedov, Denis; Kaski, Samuel; Corander, JukkaNeighbor embedding (NE) aims to preserve pairwise similarities between data items and has been shown to yield an effective principle for data visualization. However, even the best existing NE methods such as stochastic neighbor embedding (SNE) may leave large-scale patterns hidden, for example clusters, despite strong signals being present in the data. To address this, we propose a new cluster visualization method based on the Neighbor Embedding principle. We first present a family of Neighbor Embedding methods that generalizes SNE by using non-normalized Kullback–Leibler divergence with a scale parameter. In this family, much better cluster visualizations often appear with a parameter value different from the one corresponding to SNE. We also develop an efficient software that employs asynchronous stochastic block coordinate descent to optimize the new family of objective functions. Our experimental results demonstrate that the method consistently and substantially improves the visualization of data clusters compared with the state-of-the-art NE approaches. The code of our method is publicly available at https://github.com/rozyangno/sce. - Synergic Effect of N and Se Facilitates Photoelectric Performance in Co-Hyperdoped Silicon
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä(2024-10) Sun, Haibin; Liu, Xiaolong; Xu, Caixia; Xu, Long; Chen, Yuwei; Yang, Haima; Yang, Xing; Rao, Peng; Sun, Shengli; Zhao, LiFemtosecond-laser-fabricated black silicon has been widely used in the fields of solar cells, photodetectors, semiconductor devices, optical coatings, and quantum computing. However, the responsive spectral range limits its application in the near- to mid-infrared wavelengths. To further increase the optical responsivity in longer wavelengths, in this work, silicon (Si) was co-hyperdoped with nitrogen (N) and selenium (Se) through the deposition of Se films on Si followed by femtosecond (fs)-laser irradiation in an atmosphere of NF3. The optical and crystalline properties of the Si:N/Se were found to be influenced by the precursor Se film and laser fluence. The resulting photodetector, a product of this innovative approach, exhibited an impressive responsivity of 24.8 A/W at 840 nm and 19.8 A/W at 1060 nm, surpassing photodetectors made from Si:N, Si:S, and Si:S/Se (the latter two fabricated in SF6). These findings underscore the co-hyperdoping method’s potential in significantly improving optoelectronic device performance. - UAV-borne profiling radar for forest research
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä(2017) Chen, Yuwei; Hakala, Teemu; Karjalainen, Mika; Feng, Ziyi; Tang, Jian; Litkey, Paula; Kukko, Antero; Jaakkola, Anttoni; Hyyppä, JuhaMicrowave Radar is an attractive solution for forest mapping and inventories because microwave signals penetrates into the forest canopy and the backscattering signal can provide information regarding the whole forest structure. Satellite-borne and airborne imaging radars have been used in forest resources mapping for many decades. However, their accuracy with respect to the main forest inventory attributes substantially varies depending on the wavelength and techniques used in the estimation. Systems providing canopy backscatter as a function of canopy height are, practically speaking, missing. Therefore, there is a need for a radar system that would enable the scientific community to better understand the radar backscatter response from the forest canopy. Consequently, we undertook a research study to develop an unmanned aerial vehicle (UAV)-borne profiling (i.e., waveform) radar that could be used to improve the understanding of the radar backscatter response for forestry mapping and inventories. A frequency modulation continuous waveform (FMCW) profiling radar, termed FGI-Tomoradar, was introduced, designed and tested. One goal is the total weight of the whole system is less than 7 kg, including the radar system and georeferencing system, with centimetre-level positioning accuracy. Achieving this weight goal would enable the FGI-Tomoradar system to be installed on the Mini-UAV platform. The prototype system had all four linear polarization measuring capabilities, with bistatic configuration in Ku-band. In system performance tests in this study, FGI-Tomoradar was mounted on a manned helicopter together with a Riegl VQ-480-U laser scanner and tested in several flight campaigns performed at the Evo site, Finland. Airborne laser scanning data was simultaneously collected to investigate the differences and similarities of the outputs for the same target area for better understanding the penetration of the microwave signal into the forest canopy. Preliminary analysis confirmed that the profiling radar measures a clear signal from the canopy structure and has substantial potential to improve our understanding of radar forest mapping using the UAV platform.