Pub Date : 2019-08-23DOI: 10.1109/ICUAS.2019.8798333
Antun Ivanovic, Marko Car, M. Orsag, S. Bogdan
This paper addresses the issues of aerial manipulation and its dynamic center of mass variations by deriving a control principle capable of exploiting this disturbance as a means to stabilize the Unmanned Aerial Vehicle (UAV). A complete mathematical model of an aerial robot consisting of rotorcraft UAV body and a generic multiple degree of freedom manipulator is derived and presented. Previously developed control scheme utilizing both the rotor speed control and centroid vectoring through the mid-ranging approach is augmented with a standard position control loop. The proposed control approach is tested and verified in manual and autonomous flight experiments. We present the results of centroid vectoring control on a trajectory tracking example alongside which we provide comparison with state-of the-art approaches.
{"title":"Centroid vectoring control using aerial manipulator: Experimental results","authors":"Antun Ivanovic, Marko Car, M. Orsag, S. Bogdan","doi":"10.1109/ICUAS.2019.8798333","DOIUrl":"https://doi.org/10.1109/ICUAS.2019.8798333","url":null,"abstract":"This paper addresses the issues of aerial manipulation and its dynamic center of mass variations by deriving a control principle capable of exploiting this disturbance as a means to stabilize the Unmanned Aerial Vehicle (UAV). A complete mathematical model of an aerial robot consisting of rotorcraft UAV body and a generic multiple degree of freedom manipulator is derived and presented. Previously developed control scheme utilizing both the rotor speed control and centroid vectoring through the mid-ranging approach is augmented with a standard position control loop. The proposed control approach is tested and verified in manual and autonomous flight experiments. We present the results of centroid vectoring control on a trajectory tracking example alongside which we provide comparison with state-of the-art approaches.","PeriodicalId":426616,"journal":{"name":"2019 International Conference on Unmanned Aircraft Systems (ICUAS)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121486941","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-08-15DOI: 10.1109/ICUAS.2019.8797881
Ogbonnaya Anicho, P. Charlesworth, G. Baicher, A. Nagar, Neil Buckley
This work compares the application of Reinforcement Learning (RL) and Swarm Intelligence (SI) based methods for resolving the problem of coordinating multiple High Altitude Platform Stations (HAPS) for communications area coverage. Swarm coordination techniques are essential for developing autonomous capabilities for multiple HAPS/UAS control and management. This paper examines the performance of artificial intelligence (AI) capabilities of RL and SI for autonomous swarm coordination. In this work, it was observed that the RL approach showed superior overall peak user coverage with unpredictable coverage dips; while the SI based approach demonstrated lower coverage peaks but better coverage stability and faster convergence rates.
{"title":"Comparative Study for Coordinating Multiple Unmanned HAPS for Communications Area Coverage","authors":"Ogbonnaya Anicho, P. Charlesworth, G. Baicher, A. Nagar, Neil Buckley","doi":"10.1109/ICUAS.2019.8797881","DOIUrl":"https://doi.org/10.1109/ICUAS.2019.8797881","url":null,"abstract":"This work compares the application of Reinforcement Learning (RL) and Swarm Intelligence (SI) based methods for resolving the problem of coordinating multiple High Altitude Platform Stations (HAPS) for communications area coverage. Swarm coordination techniques are essential for developing autonomous capabilities for multiple HAPS/UAS control and management. This paper examines the performance of artificial intelligence (AI) capabilities of RL and SI for autonomous swarm coordination. In this work, it was observed that the RL approach showed superior overall peak user coverage with unpredictable coverage dips; while the SI based approach demonstrated lower coverage peaks but better coverage stability and faster convergence rates.","PeriodicalId":426616,"journal":{"name":"2019 International Conference on Unmanned Aircraft Systems (ICUAS)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115054983","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-08-15DOI: 10.1109/ICUAS.2019.8798368
V. Tofterup, Kjeld Jensen
Many Small Unmanned Aerial Systems (sUAS) are incapable of meeting the safety requirements to provide a sufficient low risk of a fatality while operating above populous areas or gatherings. A recognized mitigation of this risk is a failsafe system that in the event that the sUAS is unable to maintain stable flight, terminates the flight and activates an emergency parachute. This paper proposes a methodology for assessment of Commercial Off the Shelf parachutes for sUAS failsafe systems. The methodology encompasses the evaluation criteria for the selection of parachutes based on a user-defined Maximum Takeoff Weight and the failure scenario tests for assessment of reliability and efficiency. The current standard specification on parachutes for sUAS published by the American Society of Testing and Materials has inspired the failure scenario tests. These failure scenario tests consist of a bench/destructive test and a full power cut test. The multirotor used for test of the proposed methodology is a ∼ 2kg hexarotor. The results suggests the use of one specific parachute. Furthermore, the deployment time and impact energy have been estimated to be 1.2s and 21J, respectively. This impact energy suggests a probability of fatality of less than 0.01. This work is the first step towards selecting and evaluating parachute systems for sUAS. The proposed next steps are the refinement of the assessment of parachutes and increase of parachutes included in the failure scenario tests. Additionally, this will lead to the development of parachute recovery systems for sUAS with manual and autonomous triggering.
{"title":"A Methodology for evaluating Commercial Off The Shelf parachutes designed for sUAS failsafe systems","authors":"V. Tofterup, Kjeld Jensen","doi":"10.1109/ICUAS.2019.8798368","DOIUrl":"https://doi.org/10.1109/ICUAS.2019.8798368","url":null,"abstract":"Many Small Unmanned Aerial Systems (sUAS) are incapable of meeting the safety requirements to provide a sufficient low risk of a fatality while operating above populous areas or gatherings. A recognized mitigation of this risk is a failsafe system that in the event that the sUAS is unable to maintain stable flight, terminates the flight and activates an emergency parachute. This paper proposes a methodology for assessment of Commercial Off the Shelf parachutes for sUAS failsafe systems. The methodology encompasses the evaluation criteria for the selection of parachutes based on a user-defined Maximum Takeoff Weight and the failure scenario tests for assessment of reliability and efficiency. The current standard specification on parachutes for sUAS published by the American Society of Testing and Materials has inspired the failure scenario tests. These failure scenario tests consist of a bench/destructive test and a full power cut test. The multirotor used for test of the proposed methodology is a ∼ 2kg hexarotor. The results suggests the use of one specific parachute. Furthermore, the deployment time and impact energy have been estimated to be 1.2s and 21J, respectively. This impact energy suggests a probability of fatality of less than 0.01. This work is the first step towards selecting and evaluating parachute systems for sUAS. The proposed next steps are the refinement of the assessment of parachutes and increase of parachutes included in the failure scenario tests. Additionally, this will lead to the development of parachute recovery systems for sUAS with manual and autonomous triggering.","PeriodicalId":426616,"journal":{"name":"2019 International Conference on Unmanned Aircraft Systems (ICUAS)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127504683","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-08-15DOI: 10.1109/ICUAS.2019.8798308
A. Hasan, V. Tofterup, Kjeld Jensen
This paper presents development of model-based fail-safe modules for autonomous multirotor Unmanned Aerial Vehicles (UAVs) with safety parachute systems. The module is based on the adaptive eXogenous Kalman filter for actuator fault diagnosis. We assume all states can be measured, such that the primary goal of the filter is not the state estimation from the measurements, but the accurate reconstruction of the multirotor dynamics in real-time. Numerical simulations show the proposed diagnostic filter can be used to estimate the magnitude of the actuator faults accurately. Furthermore, based on simulated and real data recorded during a hexacopter UAV flight when its actuators experiencing complete failure, the experiment results demonstrate the effectiveness of the approach.
{"title":"Model-Based Fail-Safe Module for Autonomous Multirotor UAVs with Parachute Systems","authors":"A. Hasan, V. Tofterup, Kjeld Jensen","doi":"10.1109/ICUAS.2019.8798308","DOIUrl":"https://doi.org/10.1109/ICUAS.2019.8798308","url":null,"abstract":"This paper presents development of model-based fail-safe modules for autonomous multirotor Unmanned Aerial Vehicles (UAVs) with safety parachute systems. The module is based on the adaptive eXogenous Kalman filter for actuator fault diagnosis. We assume all states can be measured, such that the primary goal of the filter is not the state estimation from the measurements, but the accurate reconstruction of the multirotor dynamics in real-time. Numerical simulations show the proposed diagnostic filter can be used to estimate the magnitude of the actuator faults accurately. Furthermore, based on simulated and real data recorded during a hexacopter UAV flight when its actuators experiencing complete failure, the experiment results demonstrate the effectiveness of the approach.","PeriodicalId":426616,"journal":{"name":"2019 International Conference on Unmanned Aircraft Systems (ICUAS)","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133637698","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-06-17DOI: 10.1109/ICUAS.2019.8797731
C. Briese, Lukas Guenther
This paper presents a method to generate a dataset for training a deep convolutional network to detect a non cooperative unmanned aerial vehicle in video data. Deep convolutional network have shown a great potential for tasks like object detection and have been continuously improved in the last years. Still, the amount of training data is large and their generation can be complex and time consuming, especially if the appearance of the detected object is not clearly specified. The concept presented here is to train a deep convolutional neural network just with a few two dimensional images of unmanned aerial vehicle to simplify the process of generating training data. Performance of the trained network is evaluated with data from real experimental flights and compared with hand-labeled ground truth data to validate the correctness. To cover situations when the classifier fails at the detection, the output is integrated in a image processing pipeline for object tracking in order to establish a continuous tracking.
{"title":"Deep Learning with Semi-Synthetic Training Images for Detection of Non-Cooperative UAVs","authors":"C. Briese, Lukas Guenther","doi":"10.1109/ICUAS.2019.8797731","DOIUrl":"https://doi.org/10.1109/ICUAS.2019.8797731","url":null,"abstract":"This paper presents a method to generate a dataset for training a deep convolutional network to detect a non cooperative unmanned aerial vehicle in video data. Deep convolutional network have shown a great potential for tasks like object detection and have been continuously improved in the last years. Still, the amount of training data is large and their generation can be complex and time consuming, especially if the appearance of the detected object is not clearly specified. The concept presented here is to train a deep convolutional neural network just with a few two dimensional images of unmanned aerial vehicle to simplify the process of generating training data. Performance of the trained network is evaluated with data from real experimental flights and compared with hand-labeled ground truth data to validate the correctness. To cover situations when the classifier fails at the detection, the output is integrated in a image processing pipeline for object tracking in order to establish a continuous tracking.","PeriodicalId":426616,"journal":{"name":"2019 International Conference on Unmanned Aircraft Systems (ICUAS)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117252103","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-06-11DOI: 10.1109/ICUAS.2019.8798090
Woo-Hyun Ko, P. Kumar
We address the problem of traffic management of an unmanned aircraft system. In an effort to improve the performance with safety, we propose a probability-based collision resolution algorithm. The proposed algorithm analyzes the planned trajectories to calculate their collision probabilities, and modifies individual drone starting times to reduce the probability of collision, while attempting to preserve high performance. Our simulation results demonstrate that the proposed algorithm improves the performance of the drone traffic management by guaranteeing high safety with minimal modification of the starting times.
{"title":"Probability-based Collision Detection and Resolution of Planned Trajectories for Unmanned Aircraft System Traffic Management","authors":"Woo-Hyun Ko, P. Kumar","doi":"10.1109/ICUAS.2019.8798090","DOIUrl":"https://doi.org/10.1109/ICUAS.2019.8798090","url":null,"abstract":"We address the problem of traffic management of an unmanned aircraft system. In an effort to improve the performance with safety, we propose a probability-based collision resolution algorithm. The proposed algorithm analyzes the planned trajectories to calculate their collision probabilities, and modifies individual drone starting times to reduce the probability of collision, while attempting to preserve high performance. Our simulation results demonstrate that the proposed algorithm improves the performance of the drone traffic management by guaranteeing high safety with minimal modification of the starting times.","PeriodicalId":426616,"journal":{"name":"2019 International Conference on Unmanned Aircraft Systems (ICUAS)","volume":"103 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124803422","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-06-11DOI: 10.1109/ICUAS.2019.8797936
K. R. Chandra, Satadal Ghosh
In this paper, a vision-based autonomous landing system for a fixed wing unmanned aerial vehicle (UAV) is proposed for landing on a three-dimensional structure, which acts as an arrested landing mechanism and provides a strong visual cue for the camera to be detected easily. In particular, a red-colored hemispherical inflated air-bag (dome) has been considered as the visual cue in this paper. Moment-based shape descriptor called Hu-moments are leveraged for accurate detection of the dome. Characterization of these moments with horizontal and vertical distance of the UAV from the dome that is used to reliably detect the dome even at large distances is performed using software experiments. The proposed algorithm needs only a monocular camera and a processing unit on-board and hence is cost-effective and also applicable in GPS-denied environments. The proposed algorithm is simulated in a combined environment of V-Realm builder and MATLAB. Simulation results are presented to validate the presented algorithm for autonomous landing. This algorithm is also easily extendable to different colors and shapes of 3D structures.
{"title":"Hu-Moment-Based Autonomous Landing of a UAV on a Hemispherical Dome","authors":"K. R. Chandra, Satadal Ghosh","doi":"10.1109/ICUAS.2019.8797936","DOIUrl":"https://doi.org/10.1109/ICUAS.2019.8797936","url":null,"abstract":"In this paper, a vision-based autonomous landing system for a fixed wing unmanned aerial vehicle (UAV) is proposed for landing on a three-dimensional structure, which acts as an arrested landing mechanism and provides a strong visual cue for the camera to be detected easily. In particular, a red-colored hemispherical inflated air-bag (dome) has been considered as the visual cue in this paper. Moment-based shape descriptor called Hu-moments are leveraged for accurate detection of the dome. Characterization of these moments with horizontal and vertical distance of the UAV from the dome that is used to reliably detect the dome even at large distances is performed using software experiments. The proposed algorithm needs only a monocular camera and a processing unit on-board and hence is cost-effective and also applicable in GPS-denied environments. The proposed algorithm is simulated in a combined environment of V-Realm builder and MATLAB. Simulation results are presented to validate the presented algorithm for autonomous landing. This algorithm is also easily extendable to different colors and shapes of 3D structures.","PeriodicalId":426616,"journal":{"name":"2019 International Conference on Unmanned Aircraft Systems (ICUAS)","volume":"119 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116612735","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-06-11DOI: 10.1109/ICUAS.2019.8797943
Youngjun Choi, D. Pate, Simon Briceno, D. Mavris
Urban models for testing UAV path-planning algorithms commonly apply simple representations using cuboid or cylinderical shapes which may not capture the characteristics of a urban environment. To address this limitation of existing urban models, this paper presents two urban modeling techniques for an unmanned aircraft flight simulation in an urban environment. The first proposed urban modeling technique is an airborne LiDAR source-based approach that incorporates machine learning algorithms to identify the number of buildings and characterize them from the LiDAR information. The second proposed urban modeling technique is an artificial urban modeling technique without any airborne LiDAR resources that applies an adaptive spacing method, an iterative algorithm to define an artificial urban environment. Unlike the LiDAR source-based approach that creates an approximated urban model, the adaptive spacing-based urban modeling algorithm generates an artificial urban environment that is visually different from a reference city, but has similar the characteristics to it. To demonstrate the two proposed urban modeling techniques, numerical simulations are conducted using open-source datasets to construct several realistic urban models.
{"title":"Rapid and Automated Urban Modeling Techniques for UAS Applications","authors":"Youngjun Choi, D. Pate, Simon Briceno, D. Mavris","doi":"10.1109/ICUAS.2019.8797943","DOIUrl":"https://doi.org/10.1109/ICUAS.2019.8797943","url":null,"abstract":"Urban models for testing UAV path-planning algorithms commonly apply simple representations using cuboid or cylinderical shapes which may not capture the characteristics of a urban environment. To address this limitation of existing urban models, this paper presents two urban modeling techniques for an unmanned aircraft flight simulation in an urban environment. The first proposed urban modeling technique is an airborne LiDAR source-based approach that incorporates machine learning algorithms to identify the number of buildings and characterize them from the LiDAR information. The second proposed urban modeling technique is an artificial urban modeling technique without any airborne LiDAR resources that applies an adaptive spacing method, an iterative algorithm to define an artificial urban environment. Unlike the LiDAR source-based approach that creates an approximated urban model, the adaptive spacing-based urban modeling algorithm generates an artificial urban environment that is visually different from a reference city, but has similar the characteristics to it. To demonstrate the two proposed urban modeling techniques, numerical simulations are conducted using open-source datasets to construct several realistic urban models.","PeriodicalId":426616,"journal":{"name":"2019 International Conference on Unmanned Aircraft Systems (ICUAS)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128405723","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-06-11DOI: 10.1109/ICUAS.2019.8798212
H. Flanagan, Haiyang Chao, S. G. Hagerott
System identification and model based controller design is an increasingly important area for UAS research. As UASs are used in more challenging conditions, it is critical to have accurate system identification, controller design, and controller validation for improved aircraft safety. The roll controller of a flying-wing UAS is examined in this paper including aircraft system identification, controller design, and controller validation. This paper also introduces a new procedure for utilizing frequency domain analysis to identify and validate the lateral directional models and roll controller design of a UAS. Good agreement is observed between simulated roll controller performance and UAS flight test results, which showed the effectiveness of the overall system identification and control design practice.
{"title":"Model Based Roll Controller Tuning and Frequency Domain Analysis for a Flying-Wing UAS","authors":"H. Flanagan, Haiyang Chao, S. G. Hagerott","doi":"10.1109/ICUAS.2019.8798212","DOIUrl":"https://doi.org/10.1109/ICUAS.2019.8798212","url":null,"abstract":"System identification and model based controller design is an increasingly important area for UAS research. As UASs are used in more challenging conditions, it is critical to have accurate system identification, controller design, and controller validation for improved aircraft safety. The roll controller of a flying-wing UAS is examined in this paper including aircraft system identification, controller design, and controller validation. This paper also introduces a new procedure for utilizing frequency domain analysis to identify and validate the lateral directional models and roll controller design of a UAS. Good agreement is observed between simulated roll controller performance and UAS flight test results, which showed the effectiveness of the overall system identification and control design practice.","PeriodicalId":426616,"journal":{"name":"2019 International Conference on Unmanned Aircraft Systems (ICUAS)","volume":"111 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128441093","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-06-11DOI: 10.1109/ICUAS.2019.8798094
J. Alvarez-Muñoz, J. J. Castillo-Zamora, J. Escareño, I. Boussaada, F. Méndez-Barrios, O. Labbani-Igbida
The present work deals with a consensus control for a multi-agent system composed by a mini Vertical Take-off and Landing (VTOL) rotorcrafts by means of a controller based on time-delay parametrization. The VTOL system modeling is presented using the quaternion parametrization to develop the attitude-stabilizing law of the aerial robots. The vehicle position dynamics are extended to the multi-agent case where a time-delayed PID control is designed in order to achieve general consensus in terms of formation control of the system. Finally, a detailed simulation study is presented to validate the effectiveness of the proposed control strategy, where it also considered a collective interaction.
{"title":"Time-delay Control of a Multi-Rotor VTOL Multi-Agent System Towards Transport Operations","authors":"J. Alvarez-Muñoz, J. J. Castillo-Zamora, J. Escareño, I. Boussaada, F. Méndez-Barrios, O. Labbani-Igbida","doi":"10.1109/ICUAS.2019.8798094","DOIUrl":"https://doi.org/10.1109/ICUAS.2019.8798094","url":null,"abstract":"The present work deals with a consensus control for a multi-agent system composed by a mini Vertical Take-off and Landing (VTOL) rotorcrafts by means of a controller based on time-delay parametrization. The VTOL system modeling is presented using the quaternion parametrization to develop the attitude-stabilizing law of the aerial robots. The vehicle position dynamics are extended to the multi-agent case where a time-delayed PID control is designed in order to achieve general consensus in terms of formation control of the system. Finally, a detailed simulation study is presented to validate the effectiveness of the proposed control strategy, where it also considered a collective interaction.","PeriodicalId":426616,"journal":{"name":"2019 International Conference on Unmanned Aircraft Systems (ICUAS)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128749619","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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