A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
BIM-supported scan and flight planning for fully autonomous LiDAR-carrying UAVs
Abstract The Unmanned Aerial Vehicle (UAV) equipped with a Light Detection and Ranging (LiDAR) scanner provides a versatile and efficient platform for mobile laser scanning in construction-related scenarios. Recent studies on UAVs have demonstrated point-to-point navigation, yet there has been sparse investigation on scan coverage planning to fully explore a construction site, and on kinodynamic motion planning to ensure energy-efficient trajectories. This study develops a Building Information Model (BIM)-supported framework to facilitate scan planning and motion planning of autonomous LiDAR-carrying UAVs. The proposed framework selectively integrates the geometry and semantics from BIM to construct a probabilistic 3D voxel map. Then, a greedy algorithm is developed to iteratively generate waypoints with optimized coverage. After that, a collision-free guiding path is computed for traversing all the waypoints before it is further transformed into a high-degree polynomial trajectory. The proposed framework was validated in a simulated construction scenario of water treatment facilities using MATLAB and Unreal Engine 4 (UE4). The planned trajectory demonstrated smoothness, energy efficiency, and sufficient coverage. It reduced 86.17% of required moments from motors over the regular A* algorithm and achieved 91.67% scan coverage on the target facility.
Highlights Proposed a method to construct 3D maps from BIM for robotic applications. Developed a scan planning technique to optimize the coverage of UAV trajectories. Improved the kinodynamic feasibility and energy efficiency of UAV trajectories. Implemented an autonomous flight and laser scanning simulation environment. Achieved 86.17% moment reduction and 91.67% scan coverage in UAV flights.
BIM-supported scan and flight planning for fully autonomous LiDAR-carrying UAVs
Abstract The Unmanned Aerial Vehicle (UAV) equipped with a Light Detection and Ranging (LiDAR) scanner provides a versatile and efficient platform for mobile laser scanning in construction-related scenarios. Recent studies on UAVs have demonstrated point-to-point navigation, yet there has been sparse investigation on scan coverage planning to fully explore a construction site, and on kinodynamic motion planning to ensure energy-efficient trajectories. This study develops a Building Information Model (BIM)-supported framework to facilitate scan planning and motion planning of autonomous LiDAR-carrying UAVs. The proposed framework selectively integrates the geometry and semantics from BIM to construct a probabilistic 3D voxel map. Then, a greedy algorithm is developed to iteratively generate waypoints with optimized coverage. After that, a collision-free guiding path is computed for traversing all the waypoints before it is further transformed into a high-degree polynomial trajectory. The proposed framework was validated in a simulated construction scenario of water treatment facilities using MATLAB and Unreal Engine 4 (UE4). The planned trajectory demonstrated smoothness, energy efficiency, and sufficient coverage. It reduced 86.17% of required moments from motors over the regular A* algorithm and achieved 91.67% scan coverage on the target facility.
Highlights Proposed a method to construct 3D maps from BIM for robotic applications. Developed a scan planning technique to optimize the coverage of UAV trajectories. Improved the kinodynamic feasibility and energy efficiency of UAV trajectories. Implemented an autonomous flight and laser scanning simulation environment. Achieved 86.17% moment reduction and 91.67% scan coverage in UAV flights.
BIM-supported scan and flight planning for fully autonomous LiDAR-carrying UAVs
Song, Changhao (author) / Chen, Zhengyi (author) / Wang, Kai (author) / Luo, Han (author) / Cheng, Jack C.P. (author)
2022-08-10
Article (Journal)
Electronic Resource
English
UAV , LiDAR , BIM , Digital twin , Scan planning , Motion planning
LiDAR-supported Navigation of UAVs Over Urban Areas
| Online Contents | 2010
UAVs mission planning with flight level constraint using Fast Marching Square Method
| BASE | 2017
| British Library Conference Proceedings | 2019