TY - GEN
T1 - Performance Analysis of Low-Cost Solid-State LiDAR for Building Elements Point-Cloud Mapping
AU - Lo, Ying
AU - Cao, Yun
AU - Zhou, Xingyang
AU - Zhang, Cheng
AU - Chen, Min
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.
PY - 2025
Y1 - 2025
N2 - Accurate point cloud data is vital for the up-to-date representation of buildings. The use of Terrestrial Laser Scanners (TLS) has been prevalent for generating precise point clouds in the built environment. However, despite the development of scan planning algorithms to address issues such as occlusions and varying point densities, the significant costs and extensive time required for data acquisition and processing—often worsen by the lack of existing plans for scan planning—limit the practicality and cost-effectiveness of TLS. This necessitates the investigation of alternative methods for point cloud data collection. This study assesses the capabilities and limitations of low-cost solid-state LiDAR sensors, specifically the Livox Mid-360, in mapping the built environment. The sensor’s performance was benchmarked against TLS and onsite measurements, testing its mapping accuracy over distances ranging from 2 m to 8 m and on different materials including steel, wood, plastic, and concrete. The results demonstrate that the sensor achieves sub-centimeter accuracy within a 2 m range, with the highest accuracy on wood and the least on steel. These results validate the efficacy of low-cost solid-state LiDAR sensors for building modeling requiring centimeter-level accuracy, offering a more affordable and accessible solution for updating Building Information Modelling (BIM) model.
AB - Accurate point cloud data is vital for the up-to-date representation of buildings. The use of Terrestrial Laser Scanners (TLS) has been prevalent for generating precise point clouds in the built environment. However, despite the development of scan planning algorithms to address issues such as occlusions and varying point densities, the significant costs and extensive time required for data acquisition and processing—often worsen by the lack of existing plans for scan planning—limit the practicality and cost-effectiveness of TLS. This necessitates the investigation of alternative methods for point cloud data collection. This study assesses the capabilities and limitations of low-cost solid-state LiDAR sensors, specifically the Livox Mid-360, in mapping the built environment. The sensor’s performance was benchmarked against TLS and onsite measurements, testing its mapping accuracy over distances ranging from 2 m to 8 m and on different materials including steel, wood, plastic, and concrete. The results demonstrate that the sensor achieves sub-centimeter accuracy within a 2 m range, with the highest accuracy on wood and the least on steel. These results validate the efficacy of low-cost solid-state LiDAR sensors for building modeling requiring centimeter-level accuracy, offering a more affordable and accessible solution for updating Building Information Modelling (BIM) model.
KW - building mapping
KW - distance
KW - materials
KW - performance analysis
KW - solid-state LiDAR
UR - http://www.scopus.com/inward/record.url?scp=105002725498&partnerID=8YFLogxK
U2 - 10.1007/978-981-96-3949-6_25
DO - 10.1007/978-981-96-3949-6_25
M3 - Conference Proceeding
AN - SCOPUS:105002725498
SN - 9789819639489
T3 - Lecture Notes in Networks and Systems
SP - 325
EP - 338
BT - Selected Proceedings from the 2nd International Conference on Intelligent Manufacturing and Robotics, ICIMR 2024 - Advances in Intelligent Manufacturing and Robotics
A2 - Chen, Wei
A2 - Ping Tan, Andrew Huey
A2 - Luo, Yang
A2 - Huang, Long
A2 - Zhu, Yuyi
A2 - PP Abdul Majeed, Anwar
A2 - Zhang, Fan
A2 - Yan, Yuyao
A2 - Liu, Chenguang
PB - Springer Science and Business Media Deutschland GmbH
T2 - 2nd International Conference on Intelligent Manufacturing and Robotics, ICIMR 2024
Y2 - 22 August 2024 through 23 August 2024
ER -