Pub Date : 2023-06-06DOI: 10.1109/ICUAS57906.2023.10155889
Nelson Andres Sanchez O., S. D., F. De la Rosa R.
This article presents a system architecture that integrates the construction, execution, and monitoring of three-dimensional flight paths for drones using virtual reality (VR). In this work, we propose a system that allows the construction and execution of flight paths by people who lack experience in drone piloting. For this purpose, the integration of two computational modules is introduced into the system architecture. On the one hand, the VR module allows the user to define three-dimensional flight paths in a VR scenario by using Human-Drone interactive techniques, while on the other hand, the Control module performs the supervised execution of these paths in an outdoor scenario using a smartphone that connects to a drone. Therefore, a system based on this architecture was developed and tested through two types of tests. The first one involves real user interaction to evaluate the usability of these computational modules (construction, execution, and runtime monitoring of flight paths). The second type consists of precision tests that are carried out to evaluate the accuracy between the path planned in VR and the one executed in the real scenario.
{"title":"Virtual Reality and Human-Drone Interaction applied to the Construction and Execution of Flight Paths","authors":"Nelson Andres Sanchez O., S. D., F. De la Rosa R.","doi":"10.1109/ICUAS57906.2023.10155889","DOIUrl":"https://doi.org/10.1109/ICUAS57906.2023.10155889","url":null,"abstract":"This article presents a system architecture that integrates the construction, execution, and monitoring of three-dimensional flight paths for drones using virtual reality (VR). In this work, we propose a system that allows the construction and execution of flight paths by people who lack experience in drone piloting. For this purpose, the integration of two computational modules is introduced into the system architecture. On the one hand, the VR module allows the user to define three-dimensional flight paths in a VR scenario by using Human-Drone interactive techniques, while on the other hand, the Control module performs the supervised execution of these paths in an outdoor scenario using a smartphone that connects to a drone. Therefore, a system based on this architecture was developed and tested through two types of tests. The first one involves real user interaction to evaluate the usability of these computational modules (construction, execution, and runtime monitoring of flight paths). The second type consists of precision tests that are carried out to evaluate the accuracy between the path planned in VR and the one executed in the real scenario.","PeriodicalId":379073,"journal":{"name":"2023 International Conference on Unmanned Aircraft Systems (ICUAS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116721129","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 : 2023-06-06DOI: 10.1109/ICUAS57906.2023.10155972
H. Tian, S. Huang, P. F. Wang, C. Xiang, J. Cao, R. Teo
The main purpose of drone flight is to find an optimal path without colliding with obstacles. The key point is to design a search algorithm. Path planning for searching a 2-dimensional (2D) map has been studied extensively and reached a mature stage. For a higher-dimensional configuration space, it is quite challenging. In this paper, a sampling based path planning method is proposed. It uses the rapidly-exploring random trees (RRT) concept. An improved guidance is proposed for reducing the search space in the present algorithm in a 3D clutter environment. Simulation is given to show the effectiveness of the proposed method.
{"title":"Improved path planning algorithm of an informed RRT algorithm in 3D space","authors":"H. Tian, S. Huang, P. F. Wang, C. Xiang, J. Cao, R. Teo","doi":"10.1109/ICUAS57906.2023.10155972","DOIUrl":"https://doi.org/10.1109/ICUAS57906.2023.10155972","url":null,"abstract":"The main purpose of drone flight is to find an optimal path without colliding with obstacles. The key point is to design a search algorithm. Path planning for searching a 2-dimensional (2D) map has been studied extensively and reached a mature stage. For a higher-dimensional configuration space, it is quite challenging. In this paper, a sampling based path planning method is proposed. It uses the rapidly-exploring random trees (RRT) concept. An improved guidance is proposed for reducing the search space in the present algorithm in a 3D clutter environment. Simulation is given to show the effectiveness of the proposed method.","PeriodicalId":379073,"journal":{"name":"2023 International Conference on Unmanned Aircraft Systems (ICUAS)","volume":"142 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115359904","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}
This paper considers a variant of pursuit-evasion games where multiple attacker unmanned aerial vehicles (UAVs) are trying to converge on a target. The goal is to use a set of defender UAVs to save the target by ensuring they converge on the attackers before the latter converge to the target. The core challenge lies in appropriately assigning a particular defender to an attacker. The simple heuristic assignment based on Euclidean distance between the attacker and defender performs poorly. This paper presents a data-driven solution assuming that the attacker uses a known optimal control policy. We show how massive offline simulations can be leveraged to predict the optimal cost/value function incurred by the defender to converge on an attacker for a given target trajectory. We use this optimal cost/value function as a true measure of separation between an attacker and a defender. We use it as the guiding heuristic in the Hungarian algorithm for computing defender-attacker assignments. We perform extensive simulations to validate our approach wherein we couple the learned assignment with a non-linear model predictive controller to perform realistic simulations. We show that our assignment approach outperforms that based on the Euclidean heuristic in terms of the number of successful attempts by the defenders.
{"title":"Multi-agent Target Defense Game with Learned Defender to Attacker Assignment","authors":"Amith Manoharan, Prajwal Thakur, Ashutosh Kumar Singh","doi":"10.1109/ICUAS57906.2023.10156083","DOIUrl":"https://doi.org/10.1109/ICUAS57906.2023.10156083","url":null,"abstract":"This paper considers a variant of pursuit-evasion games where multiple attacker unmanned aerial vehicles (UAVs) are trying to converge on a target. The goal is to use a set of defender UAVs to save the target by ensuring they converge on the attackers before the latter converge to the target. The core challenge lies in appropriately assigning a particular defender to an attacker. The simple heuristic assignment based on Euclidean distance between the attacker and defender performs poorly. This paper presents a data-driven solution assuming that the attacker uses a known optimal control policy. We show how massive offline simulations can be leveraged to predict the optimal cost/value function incurred by the defender to converge on an attacker for a given target trajectory. We use this optimal cost/value function as a true measure of separation between an attacker and a defender. We use it as the guiding heuristic in the Hungarian algorithm for computing defender-attacker assignments. We perform extensive simulations to validate our approach wherein we couple the learned assignment with a non-linear model predictive controller to perform realistic simulations. We show that our assignment approach outperforms that based on the Euclidean heuristic in terms of the number of successful attempts by the defenders.","PeriodicalId":379073,"journal":{"name":"2023 International Conference on Unmanned Aircraft Systems (ICUAS)","volume":"53 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114108261","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 : 2023-06-06DOI: 10.1109/ICUAS57906.2023.10155895
Salvatore Marcellini, Fabio Ruggiero, V. Lippiello
This paper considers the problem of a reconnaissance mission in which a single multirotor drone must survey a given map by repetitively visiting different checkpoints. Several points of interest (POIs) are used to discretise the map, and each of them is associated with a time-varying heat value according to the specific application. In that way, each POI has a different visiting priority each time. The proposed solution considers a nonlinear model predictive control (NMPC) approach that minimises the map’s overall heat and considers several constraints related to the system dynamics and the environment (e.g., the presence of unknown obstacles). Possible applications are related to the research of gas leaks, area surveillance, patrolling, etc. The methodology is tested in a realistic simulation environment and through experiments.
{"title":"Nonlinear Model Predictive Control for Repetitive Area Reconnaissance with a Multirotor Drone","authors":"Salvatore Marcellini, Fabio Ruggiero, V. Lippiello","doi":"10.1109/ICUAS57906.2023.10155895","DOIUrl":"https://doi.org/10.1109/ICUAS57906.2023.10155895","url":null,"abstract":"This paper considers the problem of a reconnaissance mission in which a single multirotor drone must survey a given map by repetitively visiting different checkpoints. Several points of interest (POIs) are used to discretise the map, and each of them is associated with a time-varying heat value according to the specific application. In that way, each POI has a different visiting priority each time. The proposed solution considers a nonlinear model predictive control (NMPC) approach that minimises the map’s overall heat and considers several constraints related to the system dynamics and the environment (e.g., the presence of unknown obstacles). Possible applications are related to the research of gas leaks, area surveillance, patrolling, etc. The methodology is tested in a realistic simulation environment and through experiments.","PeriodicalId":379073,"journal":{"name":"2023 International Conference on Unmanned Aircraft Systems (ICUAS)","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127250586","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 : 2023-06-06DOI: 10.1109/ICUAS57906.2023.10156134
R. M. Bernardo, Luis Claudio Batista da Silva, P. F. Ferreira Rosa
The utilization of unmanned aerial vehicles (UAVs) in civilian and military applications has significantly increased in recent years. A common task associated with these applications is detecting objects of interest in images captured by onboard UAV cameras. The ongoing development of advanced deep convolutional neural network (DCNN) algorithms has substantially improved the accuracy of general image segmentation and classification. However, applying these techniques to images obtained from UAVs requires a representative dataset for enhanced performance. This paper presents a method for DCNN-based object detection, utilizing resources embedded in a 1.5kg quadrotor-type UAV. To address the lack of representative datasets for our target scope, we employed a DCNN model trained on a self-generated synthetic dataset. The proposed method has been validated through real experiments, and the results demonstrate this approach’s feasibility for real-time surveillance with fully onboard processing. Furthermore, this offers a stand-alone, portable, and cost-effective solution for surveillance tasks using a small UAV.
{"title":"UAV Embedded Real-Time Object Detection by a DCNN Model Trained on Synthetic Dataset","authors":"R. M. Bernardo, Luis Claudio Batista da Silva, P. F. Ferreira Rosa","doi":"10.1109/ICUAS57906.2023.10156134","DOIUrl":"https://doi.org/10.1109/ICUAS57906.2023.10156134","url":null,"abstract":"The utilization of unmanned aerial vehicles (UAVs) in civilian and military applications has significantly increased in recent years. A common task associated with these applications is detecting objects of interest in images captured by onboard UAV cameras. The ongoing development of advanced deep convolutional neural network (DCNN) algorithms has substantially improved the accuracy of general image segmentation and classification. However, applying these techniques to images obtained from UAVs requires a representative dataset for enhanced performance. This paper presents a method for DCNN-based object detection, utilizing resources embedded in a 1.5kg quadrotor-type UAV. To address the lack of representative datasets for our target scope, we employed a DCNN model trained on a self-generated synthetic dataset. The proposed method has been validated through real experiments, and the results demonstrate this approach’s feasibility for real-time surveillance with fully onboard processing. Furthermore, this offers a stand-alone, portable, and cost-effective solution for surveillance tasks using a small UAV.","PeriodicalId":379073,"journal":{"name":"2023 International Conference on Unmanned Aircraft Systems (ICUAS)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124895619","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 : 2023-06-06DOI: 10.1109/ICUAS57906.2023.10156556
Harshvardhan Uppaluru, Mohammad Ghufran, Aeris El Asslouj, H. Rastgoftar
Mechanics of materials is a traditional engineering course that exposes undergraduate students in a variety of engineering fields to the principles of strain and stress analysis. However, material deformation and strain have been evaluated theoretically, numerically, and empirically tested using expensive machinery and instruments. This paper describes a novel method for analyzing strain and deformation using quadrotors. We propose to treat quadrotors as a finite number of particles of a deformable body and apply the principles of continuum mechanics to illustrate the concept of axial and shear deformation in 2-D and 3-D motion spaces. The outcome from this work has the potential to significantly impact undergraduate education by bridging the gap between classroom instruction and hardware implementation and experiments using quadrotors. Therefore, we introduce a new role for quadrotors as "teachers," which provides an excellent opportunity to practice theoretical concepts of mechanics in a productive way.
{"title":"Drones Practicing Mechanics","authors":"Harshvardhan Uppaluru, Mohammad Ghufran, Aeris El Asslouj, H. Rastgoftar","doi":"10.1109/ICUAS57906.2023.10156556","DOIUrl":"https://doi.org/10.1109/ICUAS57906.2023.10156556","url":null,"abstract":"Mechanics of materials is a traditional engineering course that exposes undergraduate students in a variety of engineering fields to the principles of strain and stress analysis. However, material deformation and strain have been evaluated theoretically, numerically, and empirically tested using expensive machinery and instruments. This paper describes a novel method for analyzing strain and deformation using quadrotors. We propose to treat quadrotors as a finite number of particles of a deformable body and apply the principles of continuum mechanics to illustrate the concept of axial and shear deformation in 2-D and 3-D motion spaces. The outcome from this work has the potential to significantly impact undergraduate education by bridging the gap between classroom instruction and hardware implementation and experiments using quadrotors. Therefore, we introduce a new role for quadrotors as \"teachers,\" which provides an excellent opportunity to practice theoretical concepts of mechanics in a productive way.","PeriodicalId":379073,"journal":{"name":"2023 International Conference on Unmanned Aircraft Systems (ICUAS)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121848726","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 : 2023-06-06DOI: 10.1109/ICUAS57906.2023.10156196
Leandro José Evilásio Campos, Marco Henrique Terra, Ricardo Menotti, Roberto Santos Inoue
The efficient Kalman filter has been widely used in recent decades to obtain air navigation information in UAVs. However, for a good performance of the Kalman filter, the model that describes the system dynamics must not contain uncertainties. This paper presents the implementation of a robust Kalman filter to estimate the attitude, velocity, and position of UAVs. The robust filter considers uncertainties in the sensor models. A mathematical structure based on the solution of linear systems synthesizes the predictor-corrector robust estimation algorithm. The main contribution of this study is the proposed QR decomposition based on Givens rotation to solve the linear system. The simulated experiments used sensory data collected in Zürich-Switzerland and ground truth referencing attitude, velocity, and position. The offline simulation results express the effectiveness of the robust Kalman filter for this application, with a reduction of up to 18.9% in the estimation error, in relation to the standard Kalman filter. The proposal to use systolic arrays for numerical solutions has shown promise for implementation in parallel processing platforms, such as FPGAs.
{"title":"Systolic Array for Parallel Solution of the Robust Kalman Filter Used for Attitude and Position Estimations in UAVs","authors":"Leandro José Evilásio Campos, Marco Henrique Terra, Ricardo Menotti, Roberto Santos Inoue","doi":"10.1109/ICUAS57906.2023.10156196","DOIUrl":"https://doi.org/10.1109/ICUAS57906.2023.10156196","url":null,"abstract":"The efficient Kalman filter has been widely used in recent decades to obtain air navigation information in UAVs. However, for a good performance of the Kalman filter, the model that describes the system dynamics must not contain uncertainties. This paper presents the implementation of a robust Kalman filter to estimate the attitude, velocity, and position of UAVs. The robust filter considers uncertainties in the sensor models. A mathematical structure based on the solution of linear systems synthesizes the predictor-corrector robust estimation algorithm. The main contribution of this study is the proposed QR decomposition based on Givens rotation to solve the linear system. The simulated experiments used sensory data collected in Zürich-Switzerland and ground truth referencing attitude, velocity, and position. The offline simulation results express the effectiveness of the robust Kalman filter for this application, with a reduction of up to 18.9% in the estimation error, in relation to the standard Kalman filter. The proposal to use systolic arrays for numerical solutions has shown promise for implementation in parallel processing platforms, such as FPGAs.","PeriodicalId":379073,"journal":{"name":"2023 International Conference on Unmanned Aircraft Systems (ICUAS)","volume":"345 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121693906","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 : 2023-06-06DOI: 10.1109/ICUAS57906.2023.10156493
C. Graham, F. González, A. Sanoe
This paper develops a complex navigation solution for sequential drone swarm configuration using Partially Observable Markov Decision Process (POMDP) with the Bitcraze Crazyflie platform with a single localisation anchor. The objective being to generate a stable control system for a swarm of drones to navigate a controlled environment towards a waypoint. The POMDP solver takes observations of the drones’ real-world positions and determines specific actions based upon a network of functions designed to optimise a path towards the waypoint. Once the solver defines the next action the swarm navigates towards the selected direction sequentially. Through extensive developmental and formal testing, the developed system performs the objective with an average trajectory deviation of less than 0.1 meters with a duration of approximately 18 seconds. Deficiencies have been identified in the software control structure. This research highlights the importance of drone control and localisation redundancies for complex navigation solutions for micro-UAV swarm configurations.
{"title":"Implementation of Partial Observable Markov Decision Process (POMDP) algorithm using Bitcraze Crazyflie Drones","authors":"C. Graham, F. González, A. Sanoe","doi":"10.1109/ICUAS57906.2023.10156493","DOIUrl":"https://doi.org/10.1109/ICUAS57906.2023.10156493","url":null,"abstract":"This paper develops a complex navigation solution for sequential drone swarm configuration using Partially Observable Markov Decision Process (POMDP) with the Bitcraze Crazyflie platform with a single localisation anchor. The objective being to generate a stable control system for a swarm of drones to navigate a controlled environment towards a waypoint. The POMDP solver takes observations of the drones’ real-world positions and determines specific actions based upon a network of functions designed to optimise a path towards the waypoint. Once the solver defines the next action the swarm navigates towards the selected direction sequentially. Through extensive developmental and formal testing, the developed system performs the objective with an average trajectory deviation of less than 0.1 meters with a duration of approximately 18 seconds. Deficiencies have been identified in the software control structure. This research highlights the importance of drone control and localisation redundancies for complex navigation solutions for micro-UAV swarm configurations.","PeriodicalId":379073,"journal":{"name":"2023 International Conference on Unmanned Aircraft Systems (ICUAS)","volume":"97 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131529722","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 : 2023-06-06DOI: 10.1109/ICUAS57906.2023.10156608
Emanuele dos Santos Cardoso, Vinícius Pacheco Bacheti, M. Sarcinelli-Filho
This paper proposes the adoption of the leader-follower control paradigm as the support to control an unmanned aerial vehicle (UAV), in this case a quadrotor, in the accomplishment of a package-delivery task. The UAV takes-off from a ground vehicle, here an unmanned ground vehicle (UGV) represented by a unicycle robot, goes to the delivery point, over which it stays hovering for a while, and then goes back to the current position of the ground vehicle and lands on it, thus completing the delivery task. In the first step of the delivery task, to go to the delivery point, the delivery drone considers the delivery point as the formation leader, and composes a leader-follower formation with it, suitable to the delivery procedure. After, the delivery drone establishes a leader-follower formation with the ground vehicle, suitable to allow it to land on the ground vehicle. The main difference between these two leader-follower formations is that in the first case the leader is a static one, whereas in the second case the leader is a moving platform. Results of a real experiment, in lab scale, are also shown, which validate the adopted strategy.
{"title":"Package Delivery Based on the Leader-Follower Control Paradigm for Multirobot Systems","authors":"Emanuele dos Santos Cardoso, Vinícius Pacheco Bacheti, M. Sarcinelli-Filho","doi":"10.1109/ICUAS57906.2023.10156608","DOIUrl":"https://doi.org/10.1109/ICUAS57906.2023.10156608","url":null,"abstract":"This paper proposes the adoption of the leader-follower control paradigm as the support to control an unmanned aerial vehicle (UAV), in this case a quadrotor, in the accomplishment of a package-delivery task. The UAV takes-off from a ground vehicle, here an unmanned ground vehicle (UGV) represented by a unicycle robot, goes to the delivery point, over which it stays hovering for a while, and then goes back to the current position of the ground vehicle and lands on it, thus completing the delivery task. In the first step of the delivery task, to go to the delivery point, the delivery drone considers the delivery point as the formation leader, and composes a leader-follower formation with it, suitable to the delivery procedure. After, the delivery drone establishes a leader-follower formation with the ground vehicle, suitable to allow it to land on the ground vehicle. The main difference between these two leader-follower formations is that in the first case the leader is a static one, whereas in the second case the leader is a moving platform. Results of a real experiment, in lab scale, are also shown, which validate the adopted strategy.","PeriodicalId":379073,"journal":{"name":"2023 International Conference on Unmanned Aircraft Systems (ICUAS)","volume":"205 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124611394","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 : 2023-06-06DOI: 10.1109/ICUAS57906.2023.10156070
S. R. Nekoo, A. Ollero
The closed-loop position control of a flapping-wing flying robot (FWFR) is a challenging task. A complete six-degree-of-freedom (DoF) modeling and control design is preferable though that imposes complexity on the procedure and analysis of the oscillations in the trajectory. Another approach could be studying independent state variables of the system and designing a controller for them. This will provide the possibility of a better understanding of the dynamic, comparing to experimental data, then use this information for moving forward to complete 6-DoF modeling. In this work, a simple linear proportional closed-loop controller is proposed and analyzed for an equivalent dynamic model of the flapping-wing flying robot. The equivalent dynamic modeling considers the flapping motion as a base excitation that disturbs the system in oscillatory behavior. The frequency of the oscillation and data of the motion was obtained from previous experimental results and used in the modeling. The designed controller performed the regulation task easily and regulated the system to a series of set-point control successfully. The motivation for the selection of a proportional control is to keep the design as simple as possible to analyze the excitation and behavior of the flapping more precisely. A discussion on the transient and steady-state flight and the role of control design on them have been presented in this work.
{"title":"A Proportional Closed-loop Control for Equivalent Vertical Dynamics of Flapping-Wing Flying Robot","authors":"S. R. Nekoo, A. Ollero","doi":"10.1109/ICUAS57906.2023.10156070","DOIUrl":"https://doi.org/10.1109/ICUAS57906.2023.10156070","url":null,"abstract":"The closed-loop position control of a flapping-wing flying robot (FWFR) is a challenging task. A complete six-degree-of-freedom (DoF) modeling and control design is preferable though that imposes complexity on the procedure and analysis of the oscillations in the trajectory. Another approach could be studying independent state variables of the system and designing a controller for them. This will provide the possibility of a better understanding of the dynamic, comparing to experimental data, then use this information for moving forward to complete 6-DoF modeling. In this work, a simple linear proportional closed-loop controller is proposed and analyzed for an equivalent dynamic model of the flapping-wing flying robot. The equivalent dynamic modeling considers the flapping motion as a base excitation that disturbs the system in oscillatory behavior. The frequency of the oscillation and data of the motion was obtained from previous experimental results and used in the modeling. The designed controller performed the regulation task easily and regulated the system to a series of set-point control successfully. The motivation for the selection of a proportional control is to keep the design as simple as possible to analyze the excitation and behavior of the flapping more precisely. A discussion on the transient and steady-state flight and the role of control design on them have been presented in this work.","PeriodicalId":379073,"journal":{"name":"2023 International Conference on Unmanned Aircraft Systems (ICUAS)","volume":"287 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132727822","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：