Pub Date : 2019-06-11DOI: 10.1109/ICUAS.2019.8798292
R. Schacht-Rodríguez, J. Ponsart, C. García-Beltrán, C. Astorga-Zaragoza, D. Theilliol
In this paper, the impact of fault effects occurring in actuators on energy consumption for multirotor UAV during mission development is analyzed. The multirotors are typically powered by Lithium Polymer batteries where the total mission time depends on the energy available on board. According to battery and actuators health, the discharge rate tends to increase which decrease the flight endurance causing that battery to discharge completely without guaranteeing the fulfillment of the mission or even a safety landing. In that sense, a model able to determines the maximum energy and flight endurance is used considering the battery discharge, State of Charge (SoC) and State of Health (SoH) and its impact during the mission execution is evaluated considering the fault effects in actuators modeled as loss of effectiveness. The proposed approach is tested at simulation level considering an hexarotor UAV.
{"title":"Mission planning strategy for multirotor UAV based on flight endurance estimation*","authors":"R. Schacht-Rodríguez, J. Ponsart, C. García-Beltrán, C. Astorga-Zaragoza, D. Theilliol","doi":"10.1109/ICUAS.2019.8798292","DOIUrl":"https://doi.org/10.1109/ICUAS.2019.8798292","url":null,"abstract":"In this paper, the impact of fault effects occurring in actuators on energy consumption for multirotor UAV during mission development is analyzed. The multirotors are typically powered by Lithium Polymer batteries where the total mission time depends on the energy available on board. According to battery and actuators health, the discharge rate tends to increase which decrease the flight endurance causing that battery to discharge completely without guaranteeing the fulfillment of the mission or even a safety landing. In that sense, a model able to determines the maximum energy and flight endurance is used considering the battery discharge, State of Charge (SoC) and State of Health (SoH) and its impact during the mission execution is evaluated considering the fault effects in actuators modeled as loss of effectiveness. The proposed approach is tested at simulation level considering an hexarotor UAV.","PeriodicalId":426616,"journal":{"name":"2019 International Conference on Unmanned Aircraft Systems (ICUAS)","volume":"79 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":"126189862","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.2019.8798020
Jesse S. Wynn, T. McLain
The problem of precision landing for autonomous multirotor UAVs operating during the day and at night is studied. A vision-based approach is proposed and consists of varying-degree-of-freedom image-based visual servoing (VDOF IBVS), and a specialized landing marker. The proposed approach is validated through extensive flight testing outdoors in both daylight and after-dark conditions, and is done using a standard off-the-shelf autopilot system.
{"title":"Visual Servoing for Multirotor Precision Landing in Daylight and After-Dark Conditions","authors":"Jesse S. Wynn, T. McLain","doi":"10.1109/ICUAS.2019.8798020","DOIUrl":"https://doi.org/10.1109/ICUAS.2019.8798020","url":null,"abstract":"The problem of precision landing for autonomous multirotor UAVs operating during the day and at night is studied. A vision-based approach is proposed and consists of varying-degree-of-freedom image-based visual servoing (VDOF IBVS), and a specialized landing marker. The proposed approach is validated through extensive flight testing outdoors in both daylight and after-dark conditions, and is done using a standard off-the-shelf autopilot system.","PeriodicalId":426616,"journal":{"name":"2019 International Conference on Unmanned Aircraft Systems (ICUAS)","volume":"18 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":"122796176","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.2019.8798352
Malintha Fernando, Lantao Liu
We investigate the formation control of a team of homogeneous quadrotor aerial vehicles. We formulate the multiquadrotor formation as a rigid body that moves in the space with 4 degrees of freedom, which greatly reduces the modelling complexity. By combining a high-level coordination layer with the low-level control layer, aggressive formation motion can be achieved. The quadrotor formation is navigated to move in 3D space by following a reference trajectory that is outlined by a series of discrete waypoints specified as external inputs. We have validated our method through both simulations and real quadrotor experiments. Our results show that the quadrotor formation can move as fast as 2. 5 m/s within a confined indoor environment where the designated formations are always well maintained.
{"title":"Formation Control and Navigation of a Quadrotor Swarm","authors":"Malintha Fernando, Lantao Liu","doi":"10.1109/ICUAS.2019.8798352","DOIUrl":"https://doi.org/10.1109/ICUAS.2019.8798352","url":null,"abstract":"We investigate the formation control of a team of homogeneous quadrotor aerial vehicles. We formulate the multiquadrotor formation as a rigid body that moves in the space with 4 degrees of freedom, which greatly reduces the modelling complexity. By combining a high-level coordination layer with the low-level control layer, aggressive formation motion can be achieved. The quadrotor formation is navigated to move in 3D space by following a reference trajectory that is outlined by a series of discrete waypoints specified as external inputs. We have validated our method through both simulations and real quadrotor experiments. Our results show that the quadrotor formation can move as fast as 2. 5 m/s within a confined indoor environment where the designated formations are always well maintained.","PeriodicalId":426616,"journal":{"name":"2019 International Conference on Unmanned Aircraft Systems (ICUAS)","volume":"26 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":"114617396","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.2019.8798091
Shijie Gao, Carmelo Di Franco, Darius Carter, D. Quinn, N. Bezzo
Micro Aerial Vehicles (MAVs) and in particular quadrotors have gained a lot of attention because of their small size, stable, robust, and diverse sensing capabilities that make them perfect test beds in several safety critical operations. Shrinking these vehicles is desirable since agility increases. However, it entails smaller power sources and hence less flight time. Adding sensors on these systems also implies more energy consumption due to both the added weight and the supplied energy to the sensors. In this work, we build a framework to leverage the flow dynamic effects near surfaces to recognize grounds and ceilings during operations and to plan a trajectory while minimizing energy consumption. Our proposed framework leverages data from real experiments to model the behavior of the system near surfaces and graph theoretical approaches for energy efficient motion planning. As a result, this study indicates that i) we can detect surfaces during operations without the need of extra onboard sensors and ii) we can minimize energy consumption up to 15% when the system can fly near ground or ceiling surfaces. The proposed framework is validated with experimental results on a quadrotor UAV.
{"title":"Exploiting Ground and Ceiling Effects on Autonomous UAV Motion Planning","authors":"Shijie Gao, Carmelo Di Franco, Darius Carter, D. Quinn, N. Bezzo","doi":"10.1109/ICUAS.2019.8798091","DOIUrl":"https://doi.org/10.1109/ICUAS.2019.8798091","url":null,"abstract":"Micro Aerial Vehicles (MAVs) and in particular quadrotors have gained a lot of attention because of their small size, stable, robust, and diverse sensing capabilities that make them perfect test beds in several safety critical operations. Shrinking these vehicles is desirable since agility increases. However, it entails smaller power sources and hence less flight time. Adding sensors on these systems also implies more energy consumption due to both the added weight and the supplied energy to the sensors. In this work, we build a framework to leverage the flow dynamic effects near surfaces to recognize grounds and ceilings during operations and to plan a trajectory while minimizing energy consumption. Our proposed framework leverages data from real experiments to model the behavior of the system near surfaces and graph theoretical approaches for energy efficient motion planning. As a result, this study indicates that i) we can detect surfaces during operations without the need of extra onboard sensors and ii) we can minimize energy consumption up to 15% when the system can fly near ground or ceiling surfaces. The proposed framework is validated with experimental results on a quadrotor UAV.","PeriodicalId":426616,"journal":{"name":"2019 International Conference on Unmanned Aircraft Systems (ICUAS)","volume":"162 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":"121183675","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.2019.8797853
Weibin Gu, K. Valavanis, M. Rutherford, A. Rizzo
Model-based control (MBC) techniques have been successfully developed for flight control applications of unmanned aerial vehicles (UAVs) in recent years. However, their heavy reliance on the fidelity of the plant model coupled with high computational complexity make the design and implementation process challenging. To overcome such challenges, attention has been focused on the use of artificial neural networks (ANNs) to study complex systems since they show promise in system identification and controller design, to say the least. This survey aims to provide a literature review on combining MBC techniques with ANNs for UAV flight control, with the goal of laying the foundation for efficient controller designs with performance guarantees. A brief discussion on frequently-used ANNs is presented along with an analysis of their time complexity. Classification/comparison of existing dynamic modeling approaches and control techniques is provided. Challenging research questions and an envisaged control architecture are also posed for future development.
{"title":"A Survey of Artificial Neural Networks with Model-based Control Techniques for Flight Control of Unmanned Aerial Vehicles","authors":"Weibin Gu, K. Valavanis, M. Rutherford, A. Rizzo","doi":"10.1109/ICUAS.2019.8797853","DOIUrl":"https://doi.org/10.1109/ICUAS.2019.8797853","url":null,"abstract":"Model-based control (MBC) techniques have been successfully developed for flight control applications of unmanned aerial vehicles (UAVs) in recent years. However, their heavy reliance on the fidelity of the plant model coupled with high computational complexity make the design and implementation process challenging. To overcome such challenges, attention has been focused on the use of artificial neural networks (ANNs) to study complex systems since they show promise in system identification and controller design, to say the least. This survey aims to provide a literature review on combining MBC techniques with ANNs for UAV flight control, with the goal of laying the foundation for efficient controller designs with performance guarantees. A brief discussion on frequently-used ANNs is presented along with an analysis of their time complexity. Classification/comparison of existing dynamic modeling approaches and control techniques is provided. Challenging research questions and an envisaged control architecture are also posed for future development.","PeriodicalId":426616,"journal":{"name":"2019 International Conference on Unmanned Aircraft Systems (ICUAS)","volume":"1 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":"132182037","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.2019.8797937
T. Cabreira, P. Ferreira, Carmelo Di Franco, G. Buttazzo
Grid-based methods have been proposed to solve the Coverage Path Planning problem using Unmanned Aerial Vehicles in irregular-shaped areas since simple geometric flight patterns, such as the back-and-forth, are inefficient in this type of scenario. However, the grid-based methods usually apply simplistic cost functions and demand high computational time leading to inefficient and expensive paths, making them not usable in real-world scenarios. This paper introduces an energy-aware grid-based approach aimed at minimizing energy consumption during mapping missions over irregular-shaped areas. Our work was built upon a previously proposed grid-based approach. Here we introduce an energy-aware cost function based on an accurate energy model. The proposed approach was able to save up to 17% of energy in real flight experiments, proving that the original cost function was not capable of finding the optimal solution in terms of real energy measurements. Additional simulation experiments were also performed to state the energy savings in different irregular-shaped scenarios. As a further contribution, we also applied two pruning techniques to the original approach dropping the computation time up to 99%.
{"title":"Grid-Based Coverage Path Planning With Minimum Energy Over Irregular-Shaped Areas With Uavs","authors":"T. Cabreira, P. Ferreira, Carmelo Di Franco, G. Buttazzo","doi":"10.1109/ICUAS.2019.8797937","DOIUrl":"https://doi.org/10.1109/ICUAS.2019.8797937","url":null,"abstract":"Grid-based methods have been proposed to solve the Coverage Path Planning problem using Unmanned Aerial Vehicles in irregular-shaped areas since simple geometric flight patterns, such as the back-and-forth, are inefficient in this type of scenario. However, the grid-based methods usually apply simplistic cost functions and demand high computational time leading to inefficient and expensive paths, making them not usable in real-world scenarios. This paper introduces an energy-aware grid-based approach aimed at minimizing energy consumption during mapping missions over irregular-shaped areas. Our work was built upon a previously proposed grid-based approach. Here we introduce an energy-aware cost function based on an accurate energy model. The proposed approach was able to save up to 17% of energy in real flight experiments, proving that the original cost function was not capable of finding the optimal solution in terms of real energy measurements. Additional simulation experiments were also performed to state the energy savings in different irregular-shaped scenarios. As a further contribution, we also applied two pruning techniques to the original approach dropping the computation time up to 99%.","PeriodicalId":426616,"journal":{"name":"2019 International Conference on Unmanned Aircraft Systems (ICUAS)","volume":"17 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":"116273926","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.2019.8797949
Ruchir Patel, Eliot Rudnick-Cohen, S. Azarm, J. Herrmann
This paper describes a robust multi-UAV route planning problem in which any one of the vehicles could fail during plan execution at any visited location. The UAVs must visit a set of fixed locations; if one UAV fails, the other vehicles must cover any unvisited locations. The objective is to optimize the worst-case cost. This paper formulates the problem with a min-sum objective (minimizing the total distance traveled by all vehicles) and a min-max objective (minimizing the maximum distance traveled by any vehicle). A Genetic Algorithm (GA) was used to find approximate robust optimal solutions on seven instances. The results show that the GA was able to find solutions that have better worst-case cost than the solutions generated by other approaches that were tested.
{"title":"Robust Multi-UAV Route Planning Considering UAV Failure","authors":"Ruchir Patel, Eliot Rudnick-Cohen, S. Azarm, J. Herrmann","doi":"10.1109/ICUAS.2019.8797949","DOIUrl":"https://doi.org/10.1109/ICUAS.2019.8797949","url":null,"abstract":"This paper describes a robust multi-UAV route planning problem in which any one of the vehicles could fail during plan execution at any visited location. The UAVs must visit a set of fixed locations; if one UAV fails, the other vehicles must cover any unvisited locations. The objective is to optimize the worst-case cost. This paper formulates the problem with a min-sum objective (minimizing the total distance traveled by all vehicles) and a min-max objective (minimizing the maximum distance traveled by any vehicle). A Genetic Algorithm (GA) was used to find approximate robust optimal solutions on seven instances. The results show that the GA was able to find solutions that have better worst-case cost than the solutions generated by other approaches that were tested.","PeriodicalId":426616,"journal":{"name":"2019 International Conference on Unmanned Aircraft Systems (ICUAS)","volume":"129 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":"116540245","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.2019.8798198
J. Brossard, D. Bensoussan, R. Landry, M. Hammami
A new control method (B control) that guarantees fast and robust control for unstable invertible plants [1] has been recently proposed and tested [2], [3]. This method enables getting a time response with minimal overshoot and settling time equal to rise time while keeping good stability margins. Demonstration of this control method has been published in [4]. In the present work, we apply this control method to a non-linear model of a quadcopter. The fastest orientation dynamic of the drone is controlled separately from the translation dynamic which is slower. The performance of this B controller is compared to a μ-synthesis and PID controller. Matlab simulations show slightly better performances for B control compared to μ-synthesis in the time domain. However, μ-synthesis gives better results for steady flight in the presence of perturbations when compared to B controller, although it involves higher motor velocities. PID performance in the time domain is less than satisfactory as it evolves excessive gains.
{"title":"Robustness Studies on Quadrotor Control","authors":"J. Brossard, D. Bensoussan, R. Landry, M. Hammami","doi":"10.1109/ICUAS.2019.8798198","DOIUrl":"https://doi.org/10.1109/ICUAS.2019.8798198","url":null,"abstract":"A new control method (B control) that guarantees fast and robust control for unstable invertible plants [1] has been recently proposed and tested [2], [3]. This method enables getting a time response with minimal overshoot and settling time equal to rise time while keeping good stability margins. Demonstration of this control method has been published in [4]. In the present work, we apply this control method to a non-linear model of a quadcopter. The fastest orientation dynamic of the drone is controlled separately from the translation dynamic which is slower. The performance of this B controller is compared to a μ-synthesis and PID controller. Matlab simulations show slightly better performances for B control compared to μ-synthesis in the time domain. However, μ-synthesis gives better results for steady flight in the presence of perturbations when compared to B controller, although it involves higher motor velocities. PID performance in the time domain is less than satisfactory as it evolves excessive gains.","PeriodicalId":426616,"journal":{"name":"2019 International Conference on Unmanned Aircraft Systems (ICUAS)","volume":"74 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":"131799283","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.2019.8797950
Younghoon Choi, Youngjun Choi, Simon Briceno, D. Mavris
A UAS-based disaster management method has been adopted to monitor the disaster impact and protect human lives since it can be rapidly deployed, execute an aerial imaging mission, and provide a cost-efficient operation. In the case of a wildfire disaster, a disaster management is highly complex because of large-scale wildfires that can occur simultaneously and disjointly in a large area. In order to effectively manage these large-scale wildfires, it requires multiple UAS with multiple ground stations. However, conventional UAS-based management methods relies on a single ground station that can have a limitation to handle the large-scale wildfire problem. This paper presents a new path-planning framework for UAS operations including a fleet of UAVs and multiple ground stations. The framework consists of two parts: creating coverage paths for each wildfire and optimizing routes for each UAV. To test the developed framework, this paper uses representative wildfire scenarios in the State of California.
{"title":"Multi-UAS Path-Planning for a Large-scale Disjoint Disaster Management","authors":"Younghoon Choi, Youngjun Choi, Simon Briceno, D. Mavris","doi":"10.1109/ICUAS.2019.8797950","DOIUrl":"https://doi.org/10.1109/ICUAS.2019.8797950","url":null,"abstract":"A UAS-based disaster management method has been adopted to monitor the disaster impact and protect human lives since it can be rapidly deployed, execute an aerial imaging mission, and provide a cost-efficient operation. In the case of a wildfire disaster, a disaster management is highly complex because of large-scale wildfires that can occur simultaneously and disjointly in a large area. In order to effectively manage these large-scale wildfires, it requires multiple UAS with multiple ground stations. However, conventional UAS-based management methods relies on a single ground station that can have a limitation to handle the large-scale wildfire problem. This paper presents a new path-planning framework for UAS operations including a fleet of UAVs and multiple ground stations. The framework consists of two parts: creating coverage paths for each wildfire and optimizing routes for each UAV. To test the developed framework, this paper uses representative wildfire scenarios in the State of California.","PeriodicalId":426616,"journal":{"name":"2019 International Conference on Unmanned Aircraft Systems (ICUAS)","volume":"9 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":"124112970","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.2019.8797707
Derek Hollenbeck, Madoka Oyama, A. Garcia, Y. Chen
Small unmanned aircraft systems (sUAS) are becoming more and more used in atmospheric related applications as fixed remote sensors. Utilizing mobile remote sensing in air pollution applications can be beneficial. This work looks at assessing the accuracy of wind speed and direction measurements under pitch and roll maneuvers with on-board ultrasonic anemometer (UA) using sUAS. A low-cost wind tunnel (LCWT) is used as a first approach to assess this accuracy and the experimental results are compared with ground truth measurements to provide a recommendation for use in the field.
{"title":"Pitch and Roll Effects of On-board Wind Measurements Using sUAS","authors":"Derek Hollenbeck, Madoka Oyama, A. Garcia, Y. Chen","doi":"10.1109/ICUAS.2019.8797707","DOIUrl":"https://doi.org/10.1109/ICUAS.2019.8797707","url":null,"abstract":"Small unmanned aircraft systems (sUAS) are becoming more and more used in atmospheric related applications as fixed remote sensors. Utilizing mobile remote sensing in air pollution applications can be beneficial. This work looks at assessing the accuracy of wind speed and direction measurements under pitch and roll maneuvers with on-board ultrasonic anemometer (UA) using sUAS. A low-cost wind tunnel (LCWT) is used as a first approach to assess this accuracy and the experimental results are compared with ground truth measurements to provide a recommendation for use in the field.","PeriodicalId":426616,"journal":{"name":"2019 International Conference on Unmanned Aircraft Systems (ICUAS)","volume":"13 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":"124240520","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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