Scholar Hub Community:https://yscholarhub.yonsei.ac.kr/handle/2021.sw.yonsei/39912024-03-28T12:49:47Z2024-03-28T12:49:47ZAutomated Point Cloud Registration Approach Optimized for a Stop-and-Go Scanning SystemPark, SangyoonJu, SunghaNguyen, Minh HieuYoon, SanghyunHEO, JOONhttps://yscholarhub.yonsei.ac.kr/handle/2021.sw.yonsei/225952024-03-08T15:31:07Z2024-01-01T00:00:00ZTitle: Automated Point Cloud Registration Approach Optimized for a Stop-and-Go Scanning System
Authors: Park, Sangyoon; Ju, Sungha; Nguyen, Minh Hieu; Yoon, Sanghyun; HEO, JOON
Abstract: <jats:p>The latest advances in mobile platforms, such as robots, have enabled the automatic acquisition of full coverage point cloud data from large areas with terrestrial laser scanning. Despite this progress, the crucial post-processing step of registration, which aligns raw point cloud data from separate local coordinate systems into a unified coordinate system, still relies on manual intervention. To address this practical issue, this study presents an automated point cloud registration approach optimized for a stop-and-go scanning system based on a quadruped walking robot. The proposed approach comprises three main phases: perpendicular constrained wall-plane extraction; coarse registration with plane matching using point-to-point displacement calculation; and fine registration with horizontality constrained iterative closest point (ICP). Experimental results indicate that the proposed method successfully achieved automated registration with an accuracy of 0.044 m and a successful scan rate (SSR) of 100% within a time frame of 424.2 s with 18 sets of scan data acquired from the stop-and-go scanning system in a real-world indoor environment. Furthermore, it surpasses conventional approaches, ensuring reliable registration for point cloud pairs with low overlap in specific indoor environmental conditions.</jats:p>2024-01-01T00:00:00ZBIM-based scan planning for scanning with a quadruped walking robotSangyoon ParkSanghyun YoonSungha JuJoon Heohttps://yscholarhub.yonsei.ac.kr/handle/2021.sw.yonsei/67452024-03-08T15:31:03Z2023-08-01T00:00:00ZTitle: BIM-based scan planning for scanning with a quadruped walking robot
Authors: Sangyoon Park; Sanghyun Yoon; Sungha Ju; Joon Heo
Abstract: Scan positioning for documenting the geometry of an existing building still relies on the experience of an expert surveyor. Therefore, it is important to utilize optimal scan positioning for an automated scanning process with an autonomous robot platform. This study presents an automated framework to determine the optimal scan plan-ning for a stop-and-go mapping procedure with a quadruped walking robot based on BIM. The proposed framework comprises four main phases: Generation of scan-position candidates; optimal scan positioning; ordering of the optimal scan positions; data collection with an autonomous scanning system. The experimental results showed that the proposed framework presented better performance than those of the conventional ap-proaches. Furthermore, the number of scan positions and the scan operation time were significantly reduced compared with manual scanning by skilled surveyors in real-world indoor environments. A future work will focus on an automated registration process and enhancement of computational performance.2023-08-01T00:00:00ZEmerging trends in role and significance of biochar in gaseous biofuels productionSirohi, RanjnaVivekanand, V.Pandey, Ashutosh KumarTarafdar, AyonAwasthi, Mukesh KumarShakya, AmitaKim, Sang HyounSim, Sang JunTuan, Hoang A.Pandey, Ashokhttps://yscholarhub.yonsei.ac.kr/handle/2021.sw.yonsei/63802024-03-08T15:25:42Z2023-05-01T00:00:00ZTitle: Emerging trends in role and significance of biochar in gaseous biofuels production
Authors: Sirohi, Ranjna; Vivekanand, V.; Pandey, Ashutosh Kumar; Tarafdar, Ayon; Awasthi, Mukesh Kumar; Shakya, Amita; Kim, Sang Hyoun; Sim, Sang Jun; Tuan, Hoang A.; Pandey, Ashok2023-05-01T00:00:00ZPredicting the impact of hydraulic retention time and biodegradability on the performance of sludge acidogenesis using an artificial neural networkKumar Pandey, AshutoshPark, JungsuMuhorakeye, AliceMorya, RajKim, Sang-Hyounhttps://yscholarhub.yonsei.ac.kr/handle/2021.sw.yonsei/64412024-03-08T15:25:52Z2023-03-01T00:00:00ZTitle: Predicting the impact of hydraulic retention time and biodegradability on the performance of sludge acidogenesis using an artificial neural network
Authors: Kumar Pandey, Ashutosh; Park, Jungsu; Muhorakeye, Alice; Morya, Raj; Kim, Sang-Hyoun2023-03-01T00:00:00Z