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Автор: Grafiati
Опубліковано: 6 вересня 2023

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Статті в журналах з теми "UAV collision avoidance"

1

Shan, Lin, Huan-Bang Li, Ryu Miura, Takashi Matsuda, and Takeshi Matsumura. "A Novel Collision Avoidance Strategy with D2D Communications for UAV Systems." Drones 7, no. 5 (April 22, 2023): 283. http://dx.doi.org/10.3390/drones7050283.

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Анотація:
In recent years, safety operation issues related to the autonomous flight of unmanned aerial vehicles (UAVs) have become popular research and development topics worldwide. Among all UAV applications, multiple UAV-related applications are emerging due to the integration of UAVs into 6G networks, which is an important topic for next-generation wireless communication systems. For multiple UAV applications, flight safety among UAVs is the most significant issue. Therefore, collision avoidance for UAVs has become an emerging topic in UAV-related research. In the past, although many UAV collision avoidance methods have been proposed, there is still a probability of other problems, such as no possible avoidance route and unmanaged UAVs that are without centralized control, which both result in an unpredictable risk of collisions. In this study, we investigate the current existing methods and propose novel collision avoidance methods based on the elastic collision principle. To verify the performance of the proposed methods, we also conduct simulations in this paper to demonstrate their effectiveness. From the simulation results, it can be seen that the proposed methods can effectively perform collision avoidance for multiple UAVs. Specifically, using the proposed methods, all UAVs can reach their destination points within reasonable time resources without any collision, validating the effectiveness of the proposed methods.
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2

Chen, C. W., P. H. Hsieh, and W. H. Lai. "APPLICATION OF DECISION TREE ON COLLISION AVOIDANCE SYSTEM DESIGN AND VERIFICATION FOR QUADCOPTER." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2/W6 (August 23, 2017): 71–75. http://dx.doi.org/10.5194/isprs-archives-xlii-2-w6-71-2017.

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The purpose of the research is to build a collision avoidance system with decision tree algorithm used for quadcopters. While the ultrasonic range finder judges the distance is in collision avoidance interval, the access will be replaced from operator to the system to control the altitude of the UAV. According to the former experiences on operating quadcopters, we can obtain the appropriate pitch angle. The UAS implement the following three motions to avoid collisions. Case1: initial slow avoidance stage, Case2: slow avoidance stage and Case3: Rapid avoidance stage. Then the training data of collision avoidance test will be transmitted to the ground station via wireless transmission module to further analysis. The entire decision tree algorithm of collision avoidance system, transmission data, and ground station have been verified in some flight tests. In the flight test, the quadcopter can implement avoidance motion in real-time and move away from obstacles steadily. In the avoidance area, the authority of the collision avoidance system is higher than the operator and implements the avoidance process. The quadcopter can successfully fly away from the obstacles in 1.92 meter per second and the minimum distance between the quadcopter and the obstacle is 1.05 meters.
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3

Tan, Chee Yong, Sunan Huang, Kok Kiong Tan, Rodney Swee Huat Teo, Wen Qi Liu, and Feng Lin. "Collision Avoidance Design on Unmanned Aerial Vehicle in 3D Space." Unmanned Systems 06, no. 04 (October 2018): 277–95. http://dx.doi.org/10.1142/s2301385018500115.

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Collision avoidance is one of the core problems in designing a multi-unmanned aerial vehicle (UAV) system. It is to ensure each UAV can reach its target without colliding with any moving or static obstacles. With increasing usage of UAVs in many application areas, research on collision avoidance algorithm has become a hot topic. Several approaches on collision avoidance have been reported. In this paper, we design a three-dimensional collision avoidance on multi-UAV systems based on the original three-dimensional velocity obstacle method.
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4

He, Renke, Ruixuan Wei, and Qirui Zhang. "UAV autonomous collision avoidance approach." Automatika 58, no. 2 (April 3, 2017): 195–204. http://dx.doi.org/10.1080/00051144.2017.1388646.

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5

Et.al, Jung Kyu Park. "UAV Collision Detection Algorithm based on Formulafor Fast Calculation." Turkish Journal of Computer and Mathematics Education (TURCOMAT) 12, no. 6 (April 10, 2021): 452–56. http://dx.doi.org/10.17762/turcomat.v12i6.1869.

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Анотація:
Collision Avoidance System (CAS) is known as a pre-collision system or a forward collision warning system, and research has first begun as a vehicle safety system. In this paper, we propose an algorithm for collision detection of UAV. The proposed algorithm uses a mathematical method and detects the collision of the UAV by modeling it in a two-dimensional plane. Using the mathematical modeling method, it is possible to determine the collision location of the UAV in advance. Experiments were conducted to measure the performance and accuracy of the proposed algorithm. In the experiment, we proceeded assuming three environments and were able to detect an accurate collision when the UAV moved. By applying the algorithm proposed in the paper to CAS, many collision accidents can be prevented. The proposed algorithm detects collisions through mathematical calculations. In addition, the movement time of the UAV was modeled in a 2D environment to shorten the calculation time.
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H. Sawalmeh, Ahmad, and Noor Shamsiah Othman. "An Overview of Collision Avoidance Approaches and Network Architecture of Unmanned Aerial Vehicles (UAVs)." International Journal of Engineering & Technology 7, no. 4.35 (November 30, 2018): 924. http://dx.doi.org/10.14419/ijet.v7i4.35.27395.

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Анотація:
As an autonomous vehicle, Unmanned Aerial Vehicles (UAVs) are subjected to several challenges. One of the challenges is for UAV to be able to avoid collision. Many collision avoidance methods have been proposed to address this issue. Furthermore, in a multi-UAV system, it is also important to address communication issue among UAVs for cooperation and collaboration. This issue can be addressed by setting up an ad-hoc network among UAVs. There is also a need to consider the challenges in the deployment of UAVs, as well as, in the development of collision avoidance methods and the establishment of communication for cooperation and collaboration in a multi-UAV system. In this paper, we present general challenges in the deployment of UAV and comparison of UAV communication services based on its operating frequency. We also present major collision avoidance approaches, and specifically discuss collision avoidance approaches that are suitable for indoor applications. We also present the Flying Ad-hoc Networks (FANET) network architecture, communication and routing protocols for each Open System Interconnection (OSI) communication layers.
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7

Lam, T. Mung, Max Mulder, and M. M. (René) van Paassen. "Haptic Interface For UAV Collision Avoidance." International Journal of Aviation Psychology 17, no. 2 (April 17, 2007): 167–95. http://dx.doi.org/10.1080/10508410701328649.

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8

Berdonosov, V. D., A. A. Zivotova, Zaw Htet Naing, and D. O. Zhuravlev. "Speed Approach for UAV Collision Avoidance." Journal of Physics: Conference Series 1015 (May 2018): 052002. http://dx.doi.org/10.1088/1742-6596/1015/5/052002.

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9

Peng, Zhihong, and Zhimin Chen. "Ground Target Tracking and Collision Avoidance for UAV Based Guidance Vector Field." Journal of Advanced Computational Intelligence and Intelligent Informatics 19, no. 2 (March 20, 2015): 277–83. http://dx.doi.org/10.20965/jaciii.2015.p0277.

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This paper focuses on ground-moving target tracking of an unmanned aerial vehicle (UAV) in the presence of static obstacles and moving threat sources. Due to a UAV is restricted by airspace restrictions and measurement limitations during flight, we derive a dynamic path planning strategy by generating guidance vector filed combined Lyapunov vector field with collision avoidance potential function to track target in standoff distance loitering pattern, and resolved collision avoidance, simultaneously. This method relies only on the current information of the UAV and target, and generates a single-step route plan in realtime. Its performance is simple, efficient, and fast and have low computational complexity. The results of numerical simulation verify the effectiveness of the tracking and collision avoidance process of the UAV.
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HARUN, MOHAMAD HANIFF, SHAHRUM SHAH ABDULLAH, MOHD SHAHRIEEL MOHD ARAS, MOHD BAZLI BAHAR, and FARIZ ALI @IBRAHIM. "3D COLLISION AVOIDANCE SYSTEM FOR UNMANNED AERIAL VEHICLE (UAV) WITH DECENTRALIZED APPROACH." IIUM Engineering Journal 24, no. 2 (July 4, 2023): 373–90. http://dx.doi.org/10.31436/iiumej.v24i2.2803.

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Анотація:
Unmanned aerial vehicles UAVs have been developed and refined for decades. Using an integrated software system, autonomous unmanned aerial vehicles (UAVs) perform missions automatically and return to a pre-programmed point. Malaysia has a lot of unoccupied airspace, yet autonomous UAV applications and research are still rare. In critical conditions, autonomous UAVs must deal with a variety of environmental and flight issues. This project involves a decentralized 3D collision avoidance system for an autonomous UAV. Ultrasonic, infrared, and laser rangefinders were chosen for the 3D collision avoidance system. The UAV's obstacle recognition and collision avoidance performance are also tested in four experiments. In various flight conditions, the 3D collision avoidance system can identify several material types and opacities by integrating selected rangefinders. Finally, the 3D collision avoidance system quickly reacts to obstacles in the X, Y, and Z axes. ABSTRAK: Kenderaan udara tanpa pemandu (UAV) telah dibangunkan dan diperhalusi selama beberapa dekad. Menggunakan sistem perisian bersepadu, kenderaan udara tanpa pemandu (UAV) autonomi melaksanakan misi secara automatik dan kembali ke titik pra-diprogramkan. Malaysia mempunyai banyak ruang udara yang tidak berpenghuni, namun aplikasi dan penyelidikan UAV autonomi masih jarang berlaku. Dalam keadaan kritikal, UAV autonomi mesti menangani pelbagai isu alam sekitar dan penerbangan. Projek ini melibatkan sistem pengelakan perlanggaran 3D terpencar untuk UAV autonomi. Pencari jarak ultrasonik, inframerah dan laser telah dipilih untuk sistem pengelakan perlanggaran 3D. Prestasi pengecaman halangan dan pengelakan perlanggaran UAV juga diuji dalam empat eksperimen. Dalam pelbagai keadaan penerbangan, sistem pengelakan perlanggaran 3D boleh mengenal pasti beberapa jenis bahan dan kelegapan dengan menyepadukan pencari jarak terpilih. Akhir sekali, sistem pengelakan perlanggaran 3D bertindak balas dengan cepat terhadap halangan dalam paksi X, Y dan Z.
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Дисертації з теми "UAV collision avoidance"

1

Patel, Amir. "UAV collision avoidance: a specific acceleration matching approach." Master's thesis, University of Cape Town, 2011. http://hdl.handle.net/11427/11582.

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An increased level of autonomy is required for future Unmanned Aerial Vehicle (UAV) missions. One of the technologies required for this to occur is an adequate sense and avoid system to enable the UAV to detect threat aircraft and take evasive action if required. This thesis investigates a collision avoidance system to satisfy a significant portion of the requirements for sense and avoid. It was hypothesised that a recently published method of UAV guidance, Specific Acceleration Matching (SAM) Control, could address the shortcomings of the current implementations. Additionally, a novel algorithm, the Linear 3D Velocity Guidance Control Algorithm (3DVGC) was developed to address the particular requirements of UAV collision avoidance.
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2

Lee, Hua. "High-Precision Geolocation Algorithms for UAV and UUV Applications in Navigation and Collision Avoidance." International Foundation for Telemetering, 2008. http://hdl.handle.net/10150/606155.

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ITC/USA 2008 Conference Proceedings / The Forty-Fourth Annual International Telemetering Conference and Technical Exhibition / October 27-30, 2008 / Town and Country Resort & Convention Center, San Diego, California
UUV homing and docking and UAV collision avoidance are two seemingly separate research topics for different applications. Upon close examination, these two are a pair of dual problems, with interesting correspondences and commonality. In this paper, we present the theoretical analysis, signal processing, and the field experiments of these two algorithms in UAV and UUV applications in homing and docking as well as collision avoidance.
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3

Brandt, Adam M. "Haptic Collision Avoidance for a Remotely Operated Quadrotor UAV in Indoor Environments." Diss., CLICK HERE for online access, 2009. http://contentdm.lib.byu.edu/ETD/image/etd3177.pdf.

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4

Jaroń, Piotr, and Mateusz Kucharczyk. "Vision System Prototype for UAV Positioning and Sparse Obstacle Detection." Thesis, Blekinge Tekniska Högskola, Sektionen för ingenjörsvetenskap, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-4663.

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For the last few years computer vision due to its low exploitation cost and great capabilities has been experiencing rapid growth. One of the research fields that benefits from it the most is the aircrafts positioning and collision avoidance. Light cameras with low energy consumption are an ideal solution for UAVs (Unmanned Aerial Vehicles) navigation systems. With the new Swedish law – unique to Europe, that allows for civil usage of UAVs that fly on altitudes up to 120 meters, the need for reliable and cheap positioning systems became even more dire. In this thesis two possible solutions for positioning problem and one for collision avoidance were proposed and analyzed. Possibility of tracking the vehicles position both from ground and from air was exploited. Camera setup for successful positioning and collision avoidance systems was defined and preliminary results for of the systems performance were presented.
Vision systems are employed more and more often in navigation of ground and air robots. Their greatest advantages are: low cost compared to other sensors, ability to capture large portion of the environment very quickly on one image frame, and their light weight, which is a great advantage for air drone navigation systems. In the thesis the problem of UAV (Unmanned Aerial Vehicle) is considered. Two different issues are tackled. First is determining the vehicles position using one down-facing or two front-facing cameras, and the other is sparse obstacle detection. Additionally, in the thesis, the camera calibration process and camera set up for navigation is discussed. Error causes and types are analyzed.
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5

Klaus, Robert Andrew. "Development of a Sense and Avoid System for Small Unmanned Aircraft Systems." BYU ScholarsArchive, 2013. https://scholarsarchive.byu.edu/etd/3761.

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Unmanned aircraft systems (UAS) represent the future of modern aviation. Over the past 10 years their use abroad by the military has become commonplace for surveillance and combat. Unfortunately, their use at home has been far more restrictive. Due to safety and regulatory concerns, UAS are prohibited from flying in the National Airspace System without special authorization from the FAA. One main reason for this is the lack of an on-board pilot to "see and avoid" other air traffic and thereby maintain the safety of the skies. Development of a comparable capability, known as "Sense and Avoid" (SAA), has therefore become a major area of focus. This research focuses on the SAA problem as it applies specifically to small UAS. Given the size, weight, and power constraints on these aircraft, current approaches fail to provide a viable option. To aid in the development of a SAA system for small UAS, various simulation and hardware tools are discussed. The modifications to the MAGICC Lab's simulation environment to provide support for multiple agents is outlined. The use of C-MEX s-Functions to improve simulation performance and code portability is also presented. For hardware tests, two RC airframes were constructed and retrofitted with autopilots to allow autonomous flight. The development of a program to interface with the ground control software and run the collision avoidance algorithms is discussed as well. Intruder sensing is accomplished using a low-power, low-resolution radar for detection and an Extended Kalman Filter (EKF) for tracking. The radar provides good measurements for range and closing speed, but bearing measurements are poor due to the low-resolution. A novel method for improving the bearing approximation using the raw radar returns is developed and tested. A four-state EKF used to track the intruder's position and trajectory is derived and used to provide estimates to the collision avoidance planner. Simulation results and results from flight tests using a simulated radar are both presented. To effectively plan collision avoidance paths a tree-branching path planner is developed. Techniques for predicting the intruder position and creating safe, collision-free paths using the estimates provided by the EKF are presented. A method for calculating the cost of flying each path is developed to allow the selection of the best candidate path. As multiple duplicate paths can be created using the branching planner, a strategy to remove these paths and greatly increase computation speed is discussed. Both simulation and hardware results are presented for validation.
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6

Degen, Shane C. "Reactive image-based collision avoidance system for unmanned aircraft systems." Thesis, Queensland University of Technology, 2011. https://eprints.qut.edu.au/46969/1/Shane_Degen_Thesis.pdf.

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Approximately 20 years have passed now since the NTSB issued its original recommendation to expedite development, certification and production of low-cost proximity warning and conflict detection systems for general aviation [1]. While some systems are in place (TCAS [2]), ¡¨see-and-avoid¡¨ remains the primary means of separation between light aircrafts sharing the national airspace. The requirement for a collision avoidance or sense-and-avoid capability onboard unmanned aircraft has been identified by leading government, industry and regulatory bodies as one of the most significant challenges facing the routine operation of unmanned aerial systems (UAS) in the national airspace system (NAS) [3, 4]. In this thesis, we propose and develop a novel image-based collision avoidance system to detect and avoid an upcoming conflict scenario (with an intruder) without first estimating or filtering range. The proposed collision avoidance system (CAS) uses relative bearing ƒÛ and angular-area subtended ƒê , estimated from an image, to form a test statistic AS C . This test statistic is used in a thresholding technique to decide if a conflict scenario is imminent. If deemed necessary, the system will command the aircraft to perform a manoeuvre based on ƒÛ and constrained by the CAS sensor field-of-view. Through the use of a simulation environment where the UAS is mathematically modelled and a flight controller developed, we show that using Monte Carlo simulations a probability of a Mid Air Collision (MAC) MAC RR or a Near Mid Air Collision (NMAC) RiskRatio can be estimated. We also show the performance gain this system has over a simplified version (bearings-only ƒÛ ). This performance gain is demonstrated in the form of a standard operating characteristic curve. Finally, it is shown that the proposed CAS performs at a level comparable to current manned aviations equivalent level of safety (ELOS) expectations for Class E airspace. In some cases, the CAS may be oversensitive in manoeuvring the owncraft when not necessary, but this constitutes a more conservative and therefore safer, flying procedures in most instances.
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7

Cosentino, Andrea. "Obstacle detection & collision avoidance system for an Unmanned Aerial Vehicle with real time trajectory generation." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2019.

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Анотація:
This thesis work presents a preliminary design of a detection and avoidance system for an Unmanned Aerial Vehicle (UAV). The code realized is capable to sense cooperative aircraft surrounding the UAV and to avoid them in a complete autonomous way. The detection of the aircraft is made by the elaboration of the information that they share in the medium. On the other hand, the generation of the trajectories to avoid the collisions is treated using a geometrical approach and dealing with different scenarios: no-moving obstacle, moving obstacle, multiple obstacles and terrain collision avoidance. With the so called point mass model, the controls to obtain the generated trajectory are found accordantly with the main literature. The proposed solution can be used for almost any kind of UAV that shall operate in civil air space.
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8

Lindsten, Fredrik. "Angle-only based collision risk assessment for unmanned aerial vehicles." Thesis, Linköping University, Department of Electrical Engineering, 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-15757.

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This thesis investigates the crucial problem of collision avoidance for autonomous vehicles.  An anti-collision system for an unmanned aerial vehicle (UAV) is studied in particular. The purpose of this system is to make sure that the own vehicle avoids collision with other aircraft in mid-air. The sensor used to track any possible threat is for a UAV limited basically to a digital video camera. This sensor can only measure the direction to an intruding vehicle, not the range, and is therefore denoted an angle-only sensor. To estimate the position and velocity of the intruder a tracking system, based on an extended Kalman filter, is used. State estimates supplied by this system are very uncertain due to the difficulties of angle-only tracking. Probabilistic methods are therefore required for risk calculation. The risk assessment module is one of the essential parts of the collision avoidance system and has the purpose of continuously evaluating the risk for collision. To do this in a probabilistic way, it is necessary to assume a probability distribution for the tracking system output. A common approach is to assume normality, more out of habit than on actual grounds. This thesis investigates the normality assumption, and it is found that the tracking output rapidly converge towards a good normal distribution approximation. The thesis furthermore investigates the actual risk assessment module to find out how the collision risk should be determined. The traditional way to do this is to focus on a critical time point (time of closest point of approach, time of maximum collision risk etc.). A recently proposed alternative is to evaluate the risk over a horizon of time. The difference between these two concepts is evaluated. An approximate computational method for integrated risk, suitable for real-time implementations, is also validated. It is shown that the risk seen over a horizon of time is much more robust to estimation accuracy than the risk from a critical time point. The integrated risk also gives a more intuitively correct result, which makes it possible to implement the risk assessment module with a direct connection to specified aviation safety rules.

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9

Boček, Michal. "Rozšíření řídicího systému modelu letadla Skydog o podporu vzdáleného a samočinného řízení Android aplikací." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2014. http://www.nusl.cz/ntk/nusl-236091.

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The thesis aims to design and implement an Android application with ability to control the autopilot of the Skydog aircraft model using the wireless telemetry. The application shall receive data from an aircraft model gathered from various installed sensors. These data shall be then processed and corresponding instructions for autopilot shall be sent back. When collision with terrain or obstacle is detected, the application shall send instructions to autopilot to avoid such collision. RRT algorithm is used to find collision-free flight trajectory. Database of known obstacles and digital terrain model are provided to application in formats XML and GeoTIFF respectively.
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10

Lai, John. "A hidden Markov model and relative entropy rate approach to vision-based dim target detection for UAV sense-and-avoid." Thesis, Queensland University of Technology, 2010. https://eprints.qut.edu.au/34462/1/John_Lai_Thesis.pdf.

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Uninhabited aerial vehicles (UAVs) are a cutting-edge technology that is at the forefront of aviation/aerospace research and development worldwide. Many consider their current military and defence applications as just a token of their enormous potential. Unlocking and fully exploiting this potential will see UAVs in a multitude of civilian applications and routinely operating alongside piloted aircraft. The key to realising the full potential of UAVs lies in addressing a host of regulatory, public relation, and technological challenges never encountered be- fore. Aircraft collision avoidance is considered to be one of the most important issues to be addressed, given its safety critical nature. The collision avoidance problem can be roughly organised into three areas: 1) Sense; 2) Detect; and 3) Avoid. Sensing is concerned with obtaining accurate and reliable information about other aircraft in the air; detection involves identifying potential collision threats based on available information; avoidance deals with the formulation and execution of appropriate manoeuvres to maintain safe separation. This thesis tackles the detection aspect of collision avoidance, via the development of a target detection algorithm that is capable of real-time operation onboard a UAV platform. One of the key challenges of the detection problem is the need to provide early warning. This translates to detecting potential threats whilst they are still far away, when their presence is likely to be obscured and hidden by noise. Another important consideration is the choice of sensors to capture target information, which has implications for the design and practical implementation of the detection algorithm. The main contributions of the thesis are: 1) the proposal of a dim target detection algorithm combining image morphology and hidden Markov model (HMM) filtering approaches; 2) the novel use of relative entropy rate (RER) concepts for HMM filter design; 3) the characterisation of algorithm detection performance based on simulated data as well as real in-flight target image data; and 4) the demonstration of the proposed algorithm's capacity for real-time target detection. We also consider the extension of HMM filtering techniques and the application of RER concepts for target heading angle estimation. In this thesis we propose a computer-vision based detection solution, due to the commercial-off-the-shelf (COTS) availability of camera hardware and the hardware's relatively low cost, power, and size requirements. The proposed target detection algorithm adopts a two-stage processing paradigm that begins with an image enhancement pre-processing stage followed by a track-before-detect (TBD) temporal processing stage that has been shown to be effective in dim target detection. We compare the performance of two candidate morphological filters for the image pre-processing stage, and propose a multiple hidden Markov model (MHMM) filter for the TBD temporal processing stage. The role of the morphological pre-processing stage is to exploit the spatial features of potential collision threats, while the MHMM filter serves to exploit the temporal characteristics or dynamics. The problem of optimising our proposed MHMM filter has been examined in detail. Our investigation has produced a novel design process for the MHMM filter that exploits information theory and entropy related concepts. The filter design process is posed as a mini-max optimisation problem based on a joint RER cost criterion. We provide proof that this joint RER cost criterion provides a bound on the conditional mean estimate (CME) performance of our MHMM filter, and this in turn establishes a strong theoretical basis connecting our filter design process to filter performance. Through this connection we can intelligently compare and optimise candidate filter models at the design stage, rather than having to resort to time consuming Monte Carlo simulations to gauge the relative performance of candidate designs. Moreover, the underlying entropy concepts are not constrained to any particular model type. This suggests that the RER concepts established here may be generalised to provide a useful design criterion for multiple model filtering approaches outside the class of HMM filters. In this thesis we also evaluate the performance of our proposed target detection algorithm under realistic operation conditions, and give consideration to the practical deployment of the detection algorithm onboard a UAV platform. Two fixed-wing UAVs were engaged to recreate various collision-course scenarios to capture highly realistic vision (from an onboard camera perspective) of the moments leading up to a collision. Based on this collected data, our proposed detection approach was able to detect targets out to distances ranging from about 400m to 900m. These distances, (with some assumptions about closing speeds and aircraft trajectories) translate to an advanced warning ahead of impact that approaches the 12.5 second response time recommended for human pilots. Furthermore, readily available graphic processing unit (GPU) based hardware is exploited for its parallel computing capabilities to demonstrate the practical feasibility of the proposed target detection algorithm. A prototype hardware-in- the-loop system has been found to be capable of achieving data processing rates sufficient for real-time operation. There is also scope for further improvement in performance through code optimisations. Overall, our proposed image-based target detection algorithm offers UAVs a cost-effective real-time target detection capability that is a step forward in ad- dressing the collision avoidance issue that is currently one of the most significant obstacles preventing widespread civilian applications of uninhabited aircraft. We also highlight that the algorithm development process has led to the discovery of a powerful multiple HMM filtering approach and a novel RER-based multiple filter design process. The utility of our multiple HMM filtering approach and RER concepts, however, extend beyond the target detection problem. This is demonstrated by our application of HMM filters and RER concepts to a heading angle estimation problem.
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Книги з теми "UAV collision avoidance"

1

Sense and avoid in UAS: Research and applications. Hoboken, NJ: Wiley, 2012.

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Частини книг з теми "UAV collision avoidance"

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Pedro, Dário, André Mora, João Carvalho, Fábio Azevedo, and José Fonseca. "ColANet: A UAV Collision Avoidance Dataset." In IFIP Advances in Information and Communication Technology, 53–62. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-45124-0_5.

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Song, Xiao Ou. "Dynamic MAC Protocol Designed for UAV Collision Avoidance System." In Advances in Intelligent Systems and Computing, 489–98. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-61566-0_44.

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Zhao, Jiannan, Xingzao Ma, Qinbing Fu, Cheng Hu, and Shigang Yue. "An LGMD Based Competitive Collision Avoidance Strategy for UAV." In IFIP Advances in Information and Communication Technology, 80–91. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-19823-7_6.

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Park, Jung Kyu, and Jaeho Kim. "Collision Avoidance Method for UAV Using A* Search Algorithm." In Advances in Intelligent, Interactive Systems and Applications, 186–93. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-02804-6_25.

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Fang, Bin, and Tefang Chen. "Research on UAV Collision Avoidance Strategy Considering Threat Levels." In Advances in Intelligent Systems and Computing, 887–97. Berlin, Heidelberg: Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-642-54927-4_85.

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Lin, Lin, Yao Cheng, Liu Zhiyong, Liu Yinchuan, and Li Nisi. "A UAV Collision Avoidance System Based on ADS-B." In Lecture Notes in Electrical Engineering, 159–67. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-7423-5_16.

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Wen, Ma, and Liang Jin. "Research on Autonomous Collision Avoidance Method of Cooperative UAV." In Lecture Notes in Electrical Engineering, 2414–22. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-19-6613-2_235.

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Pęszor, Damian, Marzena Wojciechowska, Konrad Wojciechowski, and Marcin Szender. "Fast Moving UAV Collision Avoidance Using Optical Flow and Stereovision." In Intelligent Information and Database Systems, 572–81. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-54430-4_55.

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Lancovs, Dmitrijs. "Introducing Fixed-Wing Aircraft into Cooperative UAV Collision Avoidance System." In Lecture Notes in Networks and Systems, 392–99. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-74454-4_38.

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Chi, Pei, Xuan Zhang, Kun Wu, Lili Zheng, Jiang Zhao, and Yingxun Wang. "Distributed Formation Control and Collision Avoidance for Heterogeneous UAV Swarm." In Lecture Notes in Electrical Engineering, 1837–48. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-19-6613-2_180.

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Тези доповідей конференцій з теми "UAV collision avoidance"

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Merchant, John, and Frank Pope. "Micro UAV collision avoidance." In Defense and Security Symposium, edited by Grant R. Gerhart, Douglas W. Gage, and Charles M. Shoemaker. SPIE, 2007. http://dx.doi.org/10.1117/12.718984.

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Kwag, Young K., Min S. Choi, Chul H. Jung, and Kwang Y. Hwang. "Collision Avoidance Radar for UAV." In 2006 CIE International Conference on Radar. IEEE, 2006. http://dx.doi.org/10.1109/icr.2006.343231.

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Kwag, Young K., and Chul H. Chung. "UAV based collision avoidance radar sensor." In 2007 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2007. http://dx.doi.org/10.1109/igarss.2007.4422877.

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Tony, Lima Agnel, Debasish Ghose, and Animesh Chakravarthy. "Avoidance maps: A new concept in UAV collision avoidance." In 2017 International Conference on Unmanned Aircraft Systems (ICUAS). IEEE, 2017. http://dx.doi.org/10.1109/icuas.2017.7991382.

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Tony, Lima A., Debasish Ghose, and Animesh Chakravarthy. "Precision UAV Collision Avoidance Using Computationally Efficient Avoidance Maps." In 2018 AIAA Guidance, Navigation, and Control Conference. Reston, Virginia: American Institute of Aeronautics and Astronautics, 2018. http://dx.doi.org/10.2514/6.2018-0875.

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Kay, Jacob, Yutaka Ikeda, and Ba Nguyen. "Distributed Development of Automatic Air Collision Avoidance System Using PC-based Simulation." In 1st UAV Conference. Reston, Virigina: American Institute of Aeronautics and Astronautics, 2002. http://dx.doi.org/10.2514/6.2002-3475.

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Gan, Xusheng, Yarong Wu, Pingni Liu, and Qian Wang. "Dynamic Collision Avoidance Zone Modeling Method Based on UAV Emergency Collision Avoidance Trajectory." In 2020 IEEE International Conference on Artificial Intelligence and Information Systems (ICAIIS). IEEE, 2020. http://dx.doi.org/10.1109/icaiis49377.2020.9194915.

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Lin, Zijie, Lina Castano, and Huan Xu. "UAV Collision Avoidance with Varying Trigger Time." In 2020 International Conference on Unmanned Aircraft Systems (ICUAS). IEEE, 2020. http://dx.doi.org/10.1109/icuas48674.2020.9213955.

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Krämer, Marc Steven, and Klaus-Dieter Kuhnert. "Multi-Sensor Fusion for UAV Collision Avoidance." In the 2018 2nd International Conference. New York, New York, USA: ACM Press, 2018. http://dx.doi.org/10.1145/3185066.3185081.

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Zsedrovits, Tamas, Akos Zarandy, Balint Vanek, Tamas Peni, Jozsef Bokor, and Tamas Roska. "Collision avoidance for UAV using visual detection." In 2011 IEEE International Symposium on Circuits and Systems (ISCAS). IEEE, 2011. http://dx.doi.org/10.1109/iscas.2011.5938030.

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Звіти організацій з теми "UAV collision avoidance"

1

Wilson, Mike, and Glenn Baker. Passive Collision Avoidance System for UAS. Fort Belvoir, VA: Defense Technical Information Center, September 2008. http://dx.doi.org/10.21236/ada486617.

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Padhi, Radhakant, Amit K. Tripathi, and Ramsingh G. Raja. Reactive Collision Avoidance of UAVs withStereovision Sensing. Fort Belvoir, VA: Defense Technical Information Center, January 2014. http://dx.doi.org/10.21236/ada595808.

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