Small unmanned airborne systems to support oil and gas pipeline monitoring and mapping

Acknowledgments We thank Johan Havelaar, Aeryon Labs Inc., AeronVironment Inc. and Aeronautics Inc. for kindly permitting the use of materials in Fig. 1.Peer reviewedPublisher PD

Motion Planning

Motion planning is a fundamental function in robotics and numerous intelligent machines. The global concept of planning involves multiple capabilities, such as path generation, dynamic planning, optimization, tracking, and control. This book has organized different planning topics into three general perspectives that are classified by the type of robotic applications. The chapters are a selection of recent developments in a) planning and tracking methods for unmanned aerial vehicles, b) heuristically based methods for navigation planning and routes optimization, and c) control techniques developed for path planning of autonomous wheeled platforms

Artificial intelligence architecture based on planar LIDAR scan data to detect energy pylon structures in a UAV autonomous detailed inspection process

The technological advances in Unmanned Aerial Vehicles (UAV) related to energy power structure inspection are gaining visibility in the past decade, due to the advantages of this technique compared with traditional inspection methods. In the particular case of power pylon structure and components, autonomous UAV inspection architectures are able to increase the efficacy and security of these tasks. This kind of application presents technical challenges that must be faced to build real-world solutions, especially the precise positioning and path following for the UAV during a mission. This paper aims to evaluate a novel architecture applied to a power line pylon inspection process, based on the machine learning techniques to process and identify the signal obtained from a UAV-embedded planar Light Detection and Ranging - LiDAR sensor. A simulated environment built on the GAZEBO software presents a first evaluation of the architecture. The results show an positive detection accuracy level superior to 97% using the vertical scan data and 70% using the horizontal scan data. This accuracy level indicates that the proposed architecture is proper for the development of positioning algorithms based on the LiDAR scan data of a power pylon.This work has been supported by FCT - Fundação para a Ciência e Tecnologia within the Project Scope: UIDB/05757/2020. This work has also been supported by Fundação Araucária (grant 34/2019), and by CAPES and UTFPR through stundent scholarships.info:eu-repo/semantics/publishedVersio

Proposal of an augmented reality tag uav positioning system for power line tower inspection

Autonomous inspection Unmanned Aerial Vehicle systems are an essential research area, including power line distribution inspection. Considerable efforts to solve the demanding presented in the autonomous U AV inspection process are present in technical and scientific research. One of these challenges is the precise positioning and fly control of the U AV around the energy structures, which is vital to assure the security of the operation. The most common techniques to achieve precise positioning in UAV fly are Global Positioning Systems with RealTime Kinematic. This technique demands a proper satellite signal receiving to work appropriately, sometimes hard to achieve. The present work proposes a complementary position data system based on augmented reality tags (AR Tags) to increase the reliability of the UAV fly positioning system. The system application is proposed for energy power tower inspections as an example of use. The adaptation to other inspection tasks is possible whit some small changes. Experimental results have shown that an increase in the position accuracy is accomplished with the use of this schema.info:eu-repo/semantics/publishedVersio

Cooperative UAV–UGV autonomous power pylon inspection: an investigation of cooperative outdoor vehicle positioning architecture

Realizing autonomous inspection, such as that of power distribution lines, through unmanned aerial vehicle (UAV) systems is a key research domain in robotics. In particular, the use of autonomous and semi-autonomous vehicles to execute the tasks of an inspection process can enhance the efficacy and safety of the operation; however, many technical problems, such as those pertaining to the precise positioning and path following of the vehicles, robust obstacle detection, and intelligent control, must be addressed. In this study, an innovative architecture involving an unmanned aircraft vehicle (UAV) and an unmanned ground vehicle (UGV) was examined for detailed inspections of power lines. In the proposed strategy, each vehicle provides its position information to the other, which ensures a safe inspection process. The results of real-world experiments indicate a satisfactory performance, thereby demonstrating the feasibility of the proposed approach.This research was funded by National Counsel of Technological and Scientific Development of Brazil (CNPq). The authors thank the National Counsel of Technological and Scientific Development of Brazil (CNPq); Coordination for the Improvement of Higher Level People (CAPES); and the Brazilian Ministry of Science, Technology, Innovation, and Communication (MCTIC). The authors would also like express their deepest gratitude to Control Robotics for sharing the Pioneer P3 robot for the experiments. Thanks to Leticia Cantieri for editing the experiment video.info:eu-repo/semantics/publishedVersio