scholarly journals Use of Unmanned Aerial Vehicles (UAVs) and Photogrammetry to Obtain the International Roughness Index (IRI) on Roads

2020 ◽  
Vol 10 (24) ◽  
pp. 8788
Author(s):  
Matías Prosser-Contreras ◽  
Edison Atencio ◽  
Felipe Muñoz La Rivera ◽  
Rodrigo F. Herrera
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Negative Impact ◽  
Three Dimensional ◽  
Limiting Factor ◽  
Road Maintenance ◽  
International Roughness Index ◽  
Aerial Vehicles ◽  
Roughness Index ◽  
Road Inspection ◽  
Time Required

Road inspection and maintenance require a large amount of data collection, where the main limiting factor is the time required to cover long stretches of road, having a negative impact on the optimization of the work. This article aims to identify modern tools for road maintenance and analysis. To carry out the research, recent methodologies are used to guide the work in different stages to adequately justify the processes involved. Using unmanned aerial vehicles (UAVs), cameras, and GPS, three-dimensional virtual models are reconstructed, which are useful for extracting the necessary information since they allow for accurate replication of the captured. In this way, it is possible to obtain longitudinal profiles associated with the road, and with it, the international roughness index (IRI) is calculated, which gives results within 0.1 (m/km) of the certified official results, which shows its potential use and development.

A method for autonomous collision-free navigation of a quadrotor UAV in unknown tunnel-like environments

Robotica ◽  
2021 ◽  
pp. 1-27
Author(s):  
Taha Elmokadem ◽  
Andrey V. Savkin
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Autonomous Underwater Vehicles ◽  
Three Dimensional ◽  
Underwater Vehicles ◽  
Practical Implementation ◽  
Challenging Problem ◽  
Quadrotor Uav ◽  
Navigation Algorithm ◽  
Aerial Vehicles ◽  
Quadrotor Uavs

Abstract Unmanned aerial vehicles (UAVs) have become essential tools for exploring, mapping and inspection of unknown three-dimensional (3D) tunnel-like environments which is a very challenging problem. A computationally light navigation algorithm is developed in this paper for quadrotor UAVs to autonomously guide the vehicle through such environments. It uses sensors observations to safely guide the UAV along the tunnel axis while avoiding collisions with its walls. The approach is evaluated using several computer simulations with realistic sensing models and practical implementation with a quadrotor UAV. The proposed method is also applicable to other UAV types and autonomous underwater vehicles.

scholarly journals Vision-Based Target Three-Dimensional Geolocation Using Unmanned Aerial Vehicles

2018 ◽  
Vol 65 (10) ◽  
pp. 8052-8061 ◽  
Author(s):  
Lele Zhang ◽  
Fang Deng ◽  
Jie Chen ◽  
Yingcai Bi ◽  
Swee King Phang ◽  
...  
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Three Dimensional ◽  
Aerial Vehicles

Optimized artificial potential field algorithm to multi-unmanned aerial vehicle coordinated trajectory planning and collision avoidance in three-dimensional environment

2019 ◽  
Vol 233 (16) ◽  
pp. 6032-6043 ◽  
Author(s):  
Jun Tang ◽  
Jiayi Sun ◽  
Cong Lu ◽  
Songyang Lao
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Collision Avoidance ◽  
Unmanned Aerial Vehicle ◽  
Trajectory Planning ◽  
Potential Field ◽  
Three Dimensional ◽  
Artificial Potential Field ◽  
Aerial Vehicles ◽  
Aerial Vehicle ◽  
Vehicle Trajectory

Multi-unmanned aerial vehicle trajectory planning is one of the most complex global optimum problems in multi-unmanned aerial vehicle coordinated control. Results of recent research works on trajectory planning reveal persisting theoretical and practical problems. To mitigate them, this paper proposes a novel optimized artificial potential field algorithm for multi-unmanned aerial vehicle operations in a three-dimensional dynamic space. For all purposes, this study considers the unmanned aerial vehicles and obstacles as spheres and cylinders with negative electricity, respectively, while the targets are considered spheres with positive electricity. However, the conventional artificial potential field algorithm is restricted to a single unmanned aerial vehicle trajectory planning in two-dimensional space and usually fails to ensure collision avoidance. To deal with this challenge, we propose a method with a distance factor and jump strategy to resolve common problems such as unreachable targets and ensure that the unmanned aerial vehicle does not collide into the obstacles. The method takes companion unmanned aerial vehicles as the dynamic obstacles to realize collaborative trajectory planning. Besides, the method solves jitter problems using the dynamic step adjustment method and climb strategy. It is validated in quantitative test simulation models and reasonable results are generated for a three-dimensional simulated urban environment.

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