Vision-Based Path Finding Strategy of Unmanned Aerial Vehicles for Electrical Infrastructure Purpose

In this chapter we present the development of automated visual inspection systems for electrical infrastructure. The inspection is performed using images acquired with an unmanned aerial vehicle (UAV). Through automated inspection routes, the state of the infrastructure can be evaluated and then the appropriate correcting measures be taken. The monitoring of power lines can be done using passive sensors such as cameras or active sensors such as light detection and ranging (LIDAR) cameras, image processing techniques, computer vision and control systems can then be used. Additionally, a three-dimensional (3D) reconstruction process is possible using images either offline or during the monitoring. An UAV with an onboard embedded computer is used to execute the computer vision and path planning algorithms. The work done shows that the proposed strategy aids in the automation of power line inspection

Vision based control for fixed wing UAVs inspecting locally linear infrastructure using skid-to-turn maneuvers

The following paper proposes a novel application of Skid-to-Turn maneuvers for fixed wing Unmanned Aerial Vehicles (UAVs) inspecting locally linear infrastructure. Fixed wing UAVs, following the design of manned aircraft, traditionally employ Bank-to-Turn maneuvers to change heading and thus direction of travel. Commonly overlooked is the effect these maneuvers have on downward facing body fixed sensors, which as a result of bank, point away from the feature during turns. By adopting Skid-to-Turn maneuvers, the aircraft is able change heading whilst maintaining wings level flight, thus allowing body fixed sensors to maintain a downward facing orientation. Eliminating roll also helps to improve data quality, as sensors are no longer subjected to the swinging motion induced as they pivot about an axis perpendicular to their line of sight. Traditional tracking controllers that apply an indirect approach of capturing ground based data by flying directly overhead can also see the feature off center due to steady state pitch and roll required to stay on course. An Image Based Visual Servo controller is developed to address this issue, allowing features to be directly tracked within the image plane. Performance of the proposed controller is tested against that of a Bank-to-Turn tracking controller driven by GPS derived cross track error in a simulation environment developed to simulate the field of view of a body fixed camera

Logistic Area Detection System On Unmanned Aerial Vehicle For Plantation Area

Sejak penanaman awal kelapa sawit di Indonesia pada tahun 2019 hingga saat ini, luas perkebunan kelapa sawit mengalami perkembangan yang meningkat. Indonesia merupakan salah satu komoditas produksi kelapa sawit terbesar di dunia. Karena di Indonesia terdapat beberapa perkebunan kelapa sawit yang luas, tarkadang terkendala terhadap jalur pendistribusian pupuk. Maka diperlukannya sebuah inovasi teknologi untuk pemantauan area yang sangat luas dengan waktu yang efisien. Teknologi yang cocok untuk pemantauan dan pencarian area logistik adalah dengan menggunakan pesawat tanpa awak dikarenakan penyelusuran dapat dilakukan di udara yang tidak terkendala oleh akses darat yang menyulitkan. Pemilihan pesawat tanpa awak jenis fixed wing lebih baik dibanding drone multirotor dikarenakan konsumsi daya yang rendah dan area penjelajahan yang luas. Fokus pada penelitian ini adalah untuk mencari area logistik pupuk di perkebunan. Area logistik yang dicari adalah terpal berbentuk kotak berwarna oranye dengan ukuran 2x2 m. Pada misi pencarian area logistik metode utama yang digunakan adalah pembatasan skala warna HSV. Untuk memaksimalkan proses pengamatan area logistik diperlukan sistem untuk memaksimalkan kecepatan komputasi frame dalam mendeteksi area logistik sehingga tidak menurunkan kecepatan frame yang ditampilkan. Pengujian pendeteksian area logistik menggunakan satu parameter HSV untuk menguji keandalan sistem pendeteksian dalam mencari area logistik. Pengujian dilakukan pada pagi hari pada pukul 08.00 hingga siang hari pada pukul 15.00.  Berdasarkan hasil pengujian dapat ditarik kesimpulan kecepatan komputasi dalam mendeteksi area logistik adalah 25 fps dan sistem pendeteksian dapat mendeteksi area logistik dengan rentang intensitas kecerahan 24710 lux hingga 41530 lux dengan 1 parameter HSV.Since the initial planting of oil palm in Indonesia in 1849 until 2019, the area of ​​oil palm plantations has experienced an increasing development. Indonesia is one of the largest palm oil production commodities in the world. So we need a technological innovation for monitoring a very large area in an efficient time. The technology that is suitable for monitoring and searching for logistics areas is to use unmanned aerial vehicle (uav) because searches can be carried out in the air which is not constrained by difficult ground access. The choice of fixed wing drone is better than multirotor drones due to its low power consumption and large area of ​​exploration. The focus of this research is to find a logistics area for fertilizers in plantations. The logistics area being sought is a tarp in the shape of an orange box with a size of 2x2 m. In the search mission for the logistics area, the main method used is the HSV color scale limitation. To maximize the process of observing the logistics area, a system is needed to maximize the frame computation speed in detecting the logistics area so as not to decrease the frame rate displayed. The logistics area detection test uses one HSV parameter to test the reliability of the detection system in finding a logistics area. The test was carried out in the morning at 08.00 until noon at 15.00. Based on the test results, it can be concluded that the computational speed in detecting the logistics area is 25 fps and the detection system can detect the logistics area with a brightness intensity range of 24710 lux to 41530 lux with 1 HSV parameter

Vision based control for fixed wing UAVs inspecting locally linear infrastructure using skid-to-turn maneuvers

The following paper proposes a novel application of Skid-to-Turn maneuvers for fixed wing Unmanned Aerial Vehicles (UAVs) inspecting locally linear infrastructure. Fixed wing UAVs, following the design of manned aircraft, commonly employ Bank-to-Turn ma- neuvers to change heading and thus direction of travel. Whilst effective, banking an aircraft during the inspection of ground based features hinders data collection, with body fixed sen- sors angled away from the direction of turn and a panning motion induced through roll rate that can reduce data quality. By adopting Skid-to-Turn maneuvers, the aircraft can change heading whilst maintaining wings level flight, thus allowing body fixed sensors to main- tain a downward facing orientation. An Image-Based Visual Servo controller is developed to directly control the position of features as captured by onboard inspection sensors. This improves on the indirect approach taken by other tracking controllers where a course over ground directly above the feature is assumed to capture it centered in the field of view. Performance of the proposed controller is compared against that of a Bank-to-Turn tracking controller driven by GPS derived cross track error in a simulation environment developed to replicate the field of view of a body fixed camera

Structural Health Monitoring using Unmanned Aerial Systems

The use of Structural Health Monitoring (SHM) techniques is paramount to the safety and longevity of the structures. Many fields use this approach to monitor the performance of a system through time to determine the proper time and funds associated with repair and replacement. The monitoring of these systems includes nondestructive testing techniques (NDT), sensors permanently installed on the structure, and can also rely heavily on visual inspection. Visual inspection is widely used due to the level of trust owners have in the inspection personnel, however it is time consuming, expensive, and relies heavily on the experience of the inspectors. It is for these reasons that rapid data acquisition platforms must be developed using remote sensing systems to collect, process, and display data to decision makers quickly to make well informed decisions based on quantitative data or provide information for further inspection with a contact technique for targeted inspection. The proposed multirotor Unmanned Aerial System (UAS) platform carries a multispectral imaging payload to collect data and serve as another tool in the SHM cycle. Several demonstrations were performed in a laboratory setting using UAS acquired imagery for identification and measurement of structures. Outdoor validation was completed using a simulated bridge deck and ground based setups on in service structures. Finally, static laboratory measurements were obtained using multispectral patterns to obtain multiscale deformation measurements that will be required for use on a UAS. The novel multiscale, multispectral image analysis using UAS acquired imagery demonstrates the value of the remote sensing system as a nondestructive testing platform and tool for SHM.Ph.D., Mechanical Engineering and Mechanics -- Drexel University, 201