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[IEEE 2018 5th IEEE International Workshop on Metrology for AeroSpace (MetroAeroSpace) - Rome, Italy (2018.6.20-2018.6.22)] 2018 5th IEEE International Workshop on Metrology for AeroSpace (MetroAeroSpace) - Characterization and Testing of a High-Resolution Time-of-Flight Camera for Autonomous Navigation
摘要： This paper presents the results of research activities carried out to characterize and test the operation of a latest generation commercial, high-resolution Time-of-Flight (TOF) camera. The aim is to preliminary evaluate the achievable performance as well as potential limitations related to the use of this instrument for autonomous navigation purposes. Two fields of investigation have been identified: autonomous navigation of Unmanned Aerial Vehicles flying in GPS-denied environments; autonomous relative navigation between non-cooperative space objects. With reference to these applications, first, a metrological characterization has been operated within a laboratory setup. Second, experimental tests have been carried out by processing point clouds acquired by the TOF sensor with state-of-the-art algorithms (for depth-based odometry and non-cooperative pose determination, respectively).
关键词： depth-based odometry,non-cooperative pose determination,TOF camera,autonomous navigation,metrological characterization
更新于2025-09-23 15:22:29
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Infrared-based Autonomous Navigation for Civil Aircraft Precision Approach and Landing
摘要： Precise navigation is a fundamental problem of aircraft safety approach and landing. However, existing methods including rotorcraft-based and fixed-wing-based cannot meet the requirements of precision approach and landing of civil aircraft in Global Position System (GPS)-denied and low visibility. This paper proposes an autonomous approach and landing navigation method whose accuracy is comparable to Inertial/ Differential GPS (DGPS) integration. This method integrates inertial data, forward looking infrared (FLIR) images and runway geographic information to estimate kinetics states of aircraft during approach and landing. Firstly, we improve an existing method to robustly detect runway, accurately extract three vertexes of runway contour from FLIR images, and synthetize virtual runway features by runway geo-information and aircraft’s pose parameters. Secondly, we propose to use real and synthetic runway features to create vision cues and integrate them with inertial data in Square-root Unscented Kalman Filter (SR-UKF) to estimate motion errors. Meanwhile, the measured motion states are corrected with the estimated state errors. Finally, we design a flight data acquisition platform equipped on a general aircraft, and use the real flight data to verify our proposed method. The experimental results demonstrate that the proposed method can run smoothly for civil aircraft precision approach and landing.
关键词： approach and landing,runway detection,Civil aircraft,infrared image,autonomous navigation
更新于2025-09-23 15:22:29
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Optimal SVC placement for Maximizing Photovoltaic Hosting Capacity in Distribution Network
摘要： High throughput phenotyping holds promise of accelerating crop breeding programs and has gained great attention in the past several years. Although many platforms for data collection, including ground and aerial vehicles, have been developed to adapt to different crops and field setups, fully autonomous ground robots have not been readily available and widely used so far. In this study, we developed a ground robot that is capable of autonomously navigating in the field. We designed a sensor mounting frame that can be modified to mount different sensors for different data collection tasks. The robot was tested in a cotton breeding field and color images of the plants were collected. We developed an algorithm to count the cotton bolls using the color images. The preliminary results demonstrated that the system was capable of collecting data autonomously without human intervention and the collected data were useful to extract phenotypic traits.
关键词： cotton,phenotyping,high throughput,autonomous navigation,ground robot
更新于2025-09-11 14:15:04
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[IEEE 2018 22nd International Conference on System Theory, Control and Computing (ICSTCC) - Sinaia, Romania (2018.10.10-2018.10.12)] 2018 22nd International Conference on System Theory, Control and Computing (ICSTCC) - Autonomous Ground Vehicle Navigation Using a Novel Visual Positioning System
摘要： In this paper a novel visual positioning system for slip correction of vehicles in GPS-denied environments based on Kalman filter is presented. Kalman filter fuses 2 sources of data; the first source of data is obtained from odometry, while a computer vision algorithm is used to obtain the second source of data. Using a plane-based pose estimation algorithm that employs four reference points and the Consensus-based Tracking and Matching algorithm (CMT) we were able to obtain pose estimation with centimeter accuracy. The four reference points correspond to the pixel coordinates of the corners of a rectangle closing a region in the roof where the camera should be pointing. Since the employed camera is mounted into the vehicle and it has eye fish lens, an image distortion correction method is used. As the CMT algorithm is robust to scale and rotations, position and orientation (POSE) estimation using computer vision is obtained even if the roof is not completely visible. Autonomous navigation of a ground wheeled vehicle was achieved using the proposed algorithm performing different courses on long period of time and no big slip was observed.
关键词： Visual Odometry,Odometry,Data Fusion,CMT,Autonomous Navigation
更新于2025-09-09 09:28:46
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A Vision-Based Approach to UAV Detection and Tracking in Cooperative Applications
摘要： This paper presents a visual-based approach that allows an Unmanned Aerial Vehicle (UAV) to detect and track a cooperative ?ying vehicle autonomously using a monocular camera. The algorithms are based on template matching and morphological ?ltering, thus being able to operate within a wide range of relative distances (i.e., from a few meters up to several tens of meters), while ensuring robustness against variations of illumination conditions, target scale and background. Furthermore, the image processing chain takes full advantage of navigation hints (i.e., relative positioning and own-ship attitude estimates) to improve the computational ef?ciency and optimize the trade-off between correct detections, false alarms and missed detections. Clearly, the required exchange of information is enabled by the cooperative nature of the formation through a reliable inter-vehicle data-link. Performance assessment is carried out by exploiting ?ight data collected during an ad hoc experimental campaign. The proposed approach is a key building block of cooperative architectures designed to improve UAV navigation performance either under nominal GNSS coverage or in GNSS-challenging environments.
关键词： autonomous navigation,morphological ?ltering,visual detection,unmanned aerial vehicles,visual tracking,template matching,cooperative UAV applications
更新于2025-09-09 09:28:46