Pub Date : 2020-02-03DOI: 10.1142/s2301385020500132
Han Xiao, Ge Xu
Though the traditional algorithms could be embedded into neural architectures with the proposed principle of [H. Xiao, Hungarian layer: Logics empowered neural architecture, arXiv: 1712.02555], the variables that only occur in the condition of branch could not be updated as a special case. To tackle this issue, we multiply the conditioned branches with Dirac symbol (i.e., [Formula: see text]), then approximate Dirac symbol with the continuous functions (e.g., [Formula: see text]). In this way, the gradients of condition-specific variables could be worked out in the back-propagation process, approximately, making a fully functional neural graph. Within our novel principle, we propose the neural decision tree (NDT), which takes simplified neural networks as decision function in each branch and employs complex neural networks to generate the output in each leaf. Extensive experiments verify our theoretical analysis and demonstrate the effectiveness of our model.
{"title":"Neural Decision Tree Towards Fully Functional Neural Graph","authors":"Han Xiao, Ge Xu","doi":"10.1142/s2301385020500132","DOIUrl":"https://doi.org/10.1142/s2301385020500132","url":null,"abstract":"Though the traditional algorithms could be embedded into neural architectures with the proposed principle of [H. Xiao, Hungarian layer: Logics empowered neural architecture, arXiv: 1712.02555], the variables that only occur in the condition of branch could not be updated as a special case. To tackle this issue, we multiply the conditioned branches with Dirac symbol (i.e., [Formula: see text]), then approximate Dirac symbol with the continuous functions (e.g., [Formula: see text]). In this way, the gradients of condition-specific variables could be worked out in the back-propagation process, approximately, making a fully functional neural graph. Within our novel principle, we propose the neural decision tree (NDT), which takes simplified neural networks as decision function in each branch and employs complex neural networks to generate the output in each leaf. Extensive experiments verify our theoretical analysis and demonstrate the effectiveness of our model.","PeriodicalId":164619,"journal":{"name":"Unmanned Syst.","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117122110","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 : 2020-01-08DOI: 10.1142/S2301385020500016
Abdul Hanif Bin Zaini, Lihua Xie
This paper proposes a low complexity distributed multi-agent coordination algorithm for agents to reach their target positions in dense traffic under limited communication. Each single-integrator a...
{"title":"Distributed Drone Traffic Coordination Using Triggered Communication","authors":"Abdul Hanif Bin Zaini, Lihua Xie","doi":"10.1142/S2301385020500016","DOIUrl":"https://doi.org/10.1142/S2301385020500016","url":null,"abstract":"This paper proposes a low complexity distributed multi-agent coordination algorithm for agents to reach their target positions in dense traffic under limited communication. Each single-integrator a...","PeriodicalId":164619,"journal":{"name":"Unmanned Syst.","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124263611","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 : 2020-01-08DOI: 10.1142/S230138502050003X
S. Mathavaraj, R. Padhi
A nonlinear robust control design approach is presented in this paper for a prototype reusable launch vehicle (RLV) during the critical re-entry phase where the margin for error is small. A nominal...
{"title":"Optimally Allocated Nonlinear Robust Control of a Reusable Launch Vehicle During Re-entry","authors":"S. Mathavaraj, R. Padhi","doi":"10.1142/S230138502050003X","DOIUrl":"https://doi.org/10.1142/S230138502050003X","url":null,"abstract":"A nonlinear robust control design approach is presented in this paper for a prototype reusable launch vehicle (RLV) during the critical re-entry phase where the margin for error is small. A nominal...","PeriodicalId":164619,"journal":{"name":"Unmanned Syst.","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130949885","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 : 2020-01-08DOI: 10.1142/S2301385020500028
S. Karpuk, Snorri Gudmundsson, V. Golubev
The research presented focuses on investigating the use of Cross-Flow Fan (CFF) as a high-lift device for a Short Take-off and Landing (STOL) aircraft. The wing-embedded fan performance analysis is...
{"title":"Feasibility Study of a Multi-Purpose Aircraft Concept with a Leading-Edge Embedded Cross-Flow Fan","authors":"S. Karpuk, Snorri Gudmundsson, V. Golubev","doi":"10.1142/S2301385020500028","DOIUrl":"https://doi.org/10.1142/S2301385020500028","url":null,"abstract":"The research presented focuses on investigating the use of Cross-Flow Fan (CFF) as a high-lift device for a Short Take-off and Landing (STOL) aircraft. The wing-embedded fan performance analysis is...","PeriodicalId":164619,"journal":{"name":"Unmanned Syst.","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125356893","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 : 2020-01-08DOI: 10.1142/s2301385020500053
Jinya Su, M. Coombes, Cunjia Liu, Yongchao Zhu, Xingyang Song, S. Fang, Lei Guo, Wen‐Hua Chen
Water stress has adverse effects on crop growth and yield, where its monitoring plays a vital role in precision crop management. This paper aims at initially exploiting the potentials of UAV aerial RGB image in crop water stress assessment by developing a simple but effective supervised learning system. Various techniques are seamlessly integrated into the system including vegetation segmentation, feature engineering, Bayesian optimization and Support Vector Machine (SVM) classifier. In particular, wheat pixels are first segmented from soil background by using the classical vegetation index thresholding. Rather than performing pixel-wise classification, pixel squares of appropriate dimension are defined as samples, from which various features for pure vegetation pixels are extracted including spectral and colour index features. SVM with Bayesian optimization is adopted as the classifier. To validate the developed system, a UAV survey is performed to collect high-resolution atop canopy RGB imageries by using DJI S1000 for the experimental wheat fields of Gucheng town, Heibei Province, China. Two levels of soil moisture were designed after seedling establishment for wheat plots by using intelligent irrigation and rain shelter, where field measurements were to obtain ground soil water ratio for each wheat plot. Comparative experiments by three-fold cross-validation demonstrate that pixel-wise classification, with a high computation load, can only achieve an accuracy of 82.8% with poor F1 score of 71.7%; however, the developed system can achieve an accuracy of 89.9% with F1 score of 87.7% by using only spectral intensities, and the accuracy can be further improved to 92.8% with F1 score of 91.5% by fusing both spectral intensities and colour index features. Future work is focused on incorporating more spectral information and advanced feature extraction algorithms to further improve the performance.
{"title":"Machine Learning-Based Crop Drought Mapping System by UAV Remote Sensing RGB Imagery","authors":"Jinya Su, M. Coombes, Cunjia Liu, Yongchao Zhu, Xingyang Song, S. Fang, Lei Guo, Wen‐Hua Chen","doi":"10.1142/s2301385020500053","DOIUrl":"https://doi.org/10.1142/s2301385020500053","url":null,"abstract":"Water stress has adverse effects on crop growth and yield, where its monitoring plays a vital role in precision crop management.\u0000This paper aims at initially exploiting the potentials of UAV aerial RGB image in crop water stress assessment by developing a\u0000simple but effective supervised learning system. Various techniques are seamlessly integrated into the system including vegetation\u0000segmentation, feature engineering, Bayesian optimization and Support Vector Machine (SVM) classifier. In particular, wheat pixels\u0000are first segmented from soil background by using the classical vegetation index thresholding. Rather than performing pixel-wise\u0000classification, pixel squares of appropriate dimension are defined as samples, from which various features for pure vegetation pixels\u0000are extracted including spectral and colour index features. SVM with Bayesian optimization is adopted as the classifier. To validate\u0000the developed system, a UAV survey is performed to collect high-resolution atop canopy RGB imageries by using DJI S1000 for\u0000the experimental wheat fields of Gucheng town, Heibei Province, China. Two levels of soil moisture were designed after seedling\u0000establishment for wheat plots by using intelligent irrigation and rain shelter, where field measurements were to obtain ground soil\u0000water ratio for each wheat plot. Comparative experiments by three-fold cross-validation demonstrate that pixel-wise classification,\u0000with a high computation load, can only achieve an accuracy of 82.8% with poor F1 score of 71.7%; however, the developed system\u0000can achieve an accuracy of 89.9% with F1 score of 87.7% by using only spectral intensities, and the accuracy can be further\u0000improved to 92.8% with F1 score of 91.5% by fusing both spectral intensities and colour index features. Future work is focused on\u0000incorporating more spectral information and advanced feature extraction algorithms to further improve the performance.","PeriodicalId":164619,"journal":{"name":"Unmanned Syst.","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114467617","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 : 2020-01-01DOI: 10.1142/s2301385020500041
G. Rigatos, P. Siano, P. Wira, K. Busawon, R. Binns
A nonlinear optimal control method is developed for autonomous truck and trailer systems. Actually, two cases are distinguished: (a) a truck and trailer system that is steered by the front wheels of its truck, (b) an autonomous fire-truck robot that is steered by both the front wheels of its truck and by the rear wheels of its trailer. The kinematic model of the autonomous vehicles undergoes linearization through Taylor series expansion. The linearization is computed at a temporary operating point that is defined at each time instant by the present value of the state vector and the last value of the control inputs vector. The linearization is based on the computation of Jacobian matrices. The modeling error due to approximate linearization is considered to be a perturbation that is compensated by the robustness of the control scheme. For the approximately linearized model of the autonomous vehicles an H-infinity feedback controller is designed. This requires the solution of an algebraic Riccati equation at each iteration of the control algorithm. The stability of the control loop is confirmed through Lyapunov analysis. It is shown that the control loop exhibits the H-infinity tracking performance which implies elevated robustness against modeling errors and external disturbances. Moreover, under moderate conditions the global asymptotic stability of the control loop is proven. Finally, to implement state estimation-based control for the autonomous vehicles, through the processing of a small number of sensor measurements, the H-infinity Kalman Filter is proposed.
{"title":"A Nonlinear H-infinity Control Approach for Autonomous Truck and Trailer Systems","authors":"G. Rigatos, P. Siano, P. Wira, K. Busawon, R. Binns","doi":"10.1142/s2301385020500041","DOIUrl":"https://doi.org/10.1142/s2301385020500041","url":null,"abstract":"A nonlinear optimal control method is developed for autonomous truck and trailer systems. Actually, two cases are distinguished: (a) a truck and trailer system that is steered by the front wheels of its truck, (b) an autonomous fire-truck robot that is steered by both the front wheels of its truck and by the rear wheels of its trailer. The kinematic model of the autonomous vehicles undergoes linearization through Taylor series expansion. The linearization is computed at a temporary operating point that is defined at each time instant by the present value of the state vector and the last value of the control inputs vector. The linearization is based on the computation of Jacobian matrices. The modeling error due to approximate linearization is considered to be a perturbation that is compensated by the robustness of the control scheme. For the approximately linearized model of the autonomous vehicles an H-infinity feedback controller is designed. This requires the solution of an algebraic Riccati equation at each iteration of the control algorithm. The stability of the control loop is confirmed through Lyapunov analysis. It is shown that the control loop exhibits the H-infinity tracking performance which implies elevated robustness against modeling errors and external disturbances. Moreover, under moderate conditions the global asymptotic stability of the control loop is proven. Finally, to implement state estimation-based control for the autonomous vehicles, through the processing of a small number of sensor measurements, the H-infinity Kalman Filter is proposed.","PeriodicalId":164619,"journal":{"name":"Unmanned Syst.","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122386525","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 : 2019-09-17DOI: 10.1142/S2301385019500079
C. Olsen, K. Kalyanam, W. Baker, D. Kunz
Autonomous unmanned vehicles are well suited for long-endurance, persistent intelligence, surveillance and reconnaissance (PISR) missions. In order to conduct missions, vehicles must implement a method of task selection. We propose the Maximal Distance Discounted & Weighted Revisit Period ([Formula: see text]) utility function as a solution. We derive [Formula: see text] as a zeroth-order approximation to an infinite horizon solution of PISR when formulated as a dynamic programming (DP) problem. We then use the DP solution to develop a heuristic utility function for autonomous task selections, with the goal of minimizing the prioritized revisit time to each task. Our function adapts to different task maps and task priorities, is scalable in the number of tasks, and is robust to the ad-hoc addition or removal of tasks. We demonstrate how the [Formula: see text] parameters influence vehicle behavior. We also prove that the policy results in steady-state task selections that are periodic and that such periodicity occurs regardless of initial conditions. We then demonstrate periodicity via numerical simulations on a set of test scenarios. We present a two-step heuristic methodology for selecting utility function parameters that deliver empirically good performance, which we demonstrate through a simulation-based comparison to a single-vehicle Traveling Salesman Problem (TSP) solution. The comparisons are based on four sample task maps designed to resemble operational scenarios.
{"title":"Maximal Distance Discounted and Weighted Revisit Period: A Utility Approach to Persistent Unmanned Surveillance","authors":"C. Olsen, K. Kalyanam, W. Baker, D. Kunz","doi":"10.1142/S2301385019500079","DOIUrl":"https://doi.org/10.1142/S2301385019500079","url":null,"abstract":"Autonomous unmanned vehicles are well suited for long-endurance, persistent intelligence, surveillance and reconnaissance (PISR) missions. In order to conduct missions, vehicles must implement a method of task selection. We propose the Maximal Distance Discounted & Weighted Revisit Period ([Formula: see text]) utility function as a solution. We derive [Formula: see text] as a zeroth-order approximation to an infinite horizon solution of PISR when formulated as a dynamic programming (DP) problem. We then use the DP solution to develop a heuristic utility function for autonomous task selections, with the goal of minimizing the prioritized revisit time to each task. Our function adapts to different task maps and task priorities, is scalable in the number of tasks, and is robust to the ad-hoc addition or removal of tasks. We demonstrate how the [Formula: see text] parameters influence vehicle behavior. We also prove that the policy results in steady-state task selections that are periodic and that such periodicity occurs regardless of initial conditions. We then demonstrate periodicity via numerical simulations on a set of test scenarios. We present a two-step heuristic methodology for selecting utility function parameters that deliver empirically good performance, which we demonstrate through a simulation-based comparison to a single-vehicle Traveling Salesman Problem (TSP) solution. The comparisons are based on four sample task maps designed to resemble operational scenarios.","PeriodicalId":164619,"journal":{"name":"Unmanned Syst.","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114226747","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 : 2019-09-17DOI: 10.1142/S2301385019500109
K. Dong, Q. Quan, W. Wonham
Autonomous Aerial Refueling (AAR) is vulnerable to various failures and involves cooperation among autonomous receivers, tankers and remote pilots. Dangerous flight maneuvers may be executed when unexpected failures or command conflicts happen. To solve this problem, a failsafe mechanism based on State Tree Structures (STS) is proposed. The failsafe mechanism is a control logic that guides what subsequent actions the autonomous receiver should take, by observing real-time information of internal low-level subsystems such as guidance and drogue&probe and external instructions from tankers and pilots. To generate such a controller using STS, the AAR procedure is decomposed into several modes, and safety issues related with seven low-level subsystems are summarized. Then common functional demands and safety requirements are textually described. On this basis, the AAR plants and specifications are modeled by STS, and a supervisor is synthesized to control the AAR model. To prove its feasibility and correctness, a simulation environment incorporating such a logic supervisor is built and tested. The design procedures presented in this paper can be used in decision-making strategies for similar flight tasks. Supporting materials can be downloaded in Github, [ https://github.com/KevinDong0810/Failsafe-Design-for-AAR-using-STS ] including related software, input documents and output files.
{"title":"Failsafe Mechanism Design for Autonomous Aerial Refueling using State Tree Structures","authors":"K. Dong, Q. Quan, W. Wonham","doi":"10.1142/S2301385019500109","DOIUrl":"https://doi.org/10.1142/S2301385019500109","url":null,"abstract":"Autonomous Aerial Refueling (AAR) is vulnerable to various failures and involves cooperation among autonomous receivers, tankers and remote pilots. Dangerous flight maneuvers may be executed when unexpected failures or command conflicts happen. To solve this problem, a failsafe mechanism based on State Tree Structures (STS) is proposed. The failsafe mechanism is a control logic that guides what subsequent actions the autonomous receiver should take, by observing real-time information of internal low-level subsystems such as guidance and drogue&probe and external instructions from tankers and pilots. To generate such a controller using STS, the AAR procedure is decomposed into several modes, and safety issues related with seven low-level subsystems are summarized. Then common functional demands and safety requirements are textually described. On this basis, the AAR plants and specifications are modeled by STS, and a supervisor is synthesized to control the AAR model. To prove its feasibility and correctness, a simulation environment incorporating such a logic supervisor is built and tested. The design procedures presented in this paper can be used in decision-making strategies for similar flight tasks. Supporting materials can be downloaded in Github, [ https://github.com/KevinDong0810/Failsafe-Design-for-AAR-using-STS ] including related software, input documents and output files.","PeriodicalId":164619,"journal":{"name":"Unmanned Syst.","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128353735","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 : 2019-09-17DOI: 10.1142/S2301385019500067
Jun En Low, D. S. B. Shaiful, Luke Thura Soe Win, G. Soh, S. Foong
In this paper, we explore a novel multi-mode hybrid Unmanned Aerial Vehicle (UAV). We combine a tailless fixed-wing with a dual-wing monocopter such that the craft’s propulsion systems and aerodynamic surfaces are fully utilized in both a horizontal cruising mode and a vertical hovering mode. This maximizes the structural efficiency across the flight envelope, thereby reducing drag and unused mass while airborne in either flight mode. This UAV is also designed such that the transition between the two flight modes can be executed in mid-air, using only its existing flight actuators and sensors — there are no transition specific actuators. Using two prototypes, the foundational design and control of the system is established; the first explores the hovering mode characteristics of the unique dual-wing monocopter configuration, while the second explores the full multi-mode capabilities of the combined platform. In addition to analytical simulations, the prototypes are experimentally evaluated and assessed to demonstrate the feasibility, viability and potential of this multi-mode aerial robot design.
{"title":"Design of a Hybrid Aerial Robot with Multi-Mode Structural Efficiency and Optimized Mid-Air Transition","authors":"Jun En Low, D. S. B. Shaiful, Luke Thura Soe Win, G. Soh, S. Foong","doi":"10.1142/S2301385019500067","DOIUrl":"https://doi.org/10.1142/S2301385019500067","url":null,"abstract":"In this paper, we explore a novel multi-mode hybrid Unmanned Aerial Vehicle (UAV). We combine a tailless fixed-wing with a dual-wing monocopter such that the craft’s propulsion systems and aerodynamic surfaces are fully utilized in both a horizontal cruising mode and a vertical hovering mode. This maximizes the structural efficiency across the flight envelope, thereby reducing drag and unused mass while airborne in either flight mode. This UAV is also designed such that the transition between the two flight modes can be executed in mid-air, using only its existing flight actuators and sensors — there are no transition specific actuators. Using two prototypes, the foundational design and control of the system is established; the first explores the hovering mode characteristics of the unique dual-wing monocopter configuration, while the second explores the full multi-mode capabilities of the combined platform. In addition to analytical simulations, the prototypes are experimentally evaluated and assessed to demonstrate the feasibility, viability and potential of this multi-mode aerial robot design.","PeriodicalId":164619,"journal":{"name":"Unmanned Syst.","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130480517","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 : 2019-09-17DOI: 10.1142/S2301385019500092
A. Weishäupl, S. Prior
This paper investigates the interference that arises from overlapping Unmanned Aerial Vehicle (UAV) propellers during hovering flight. The tests have been conducted on [Formula: see text] ultralight carbon fiber propellers using a bespoke mount and the RCBenchmark Series 1780 dynamometer at various degrees of overlap [Formula: see text] and vertical separation [Formula: see text]. A great deal of confusion regarding the losses that are associated with mounting propellers in a co-axial configuration is reported in the literature, with a summary of historical tandem helicopters having been conducted. The results highlight a region of beneficial overlap (0–20%), which has the potential to be advantageous to a wide range of UAVs.
{"title":"Influence of Propeller Overlap on Large-Scale Tandem UAV Performance","authors":"A. Weishäupl, S. Prior","doi":"10.1142/S2301385019500092","DOIUrl":"https://doi.org/10.1142/S2301385019500092","url":null,"abstract":"This paper investigates the interference that arises from overlapping Unmanned Aerial Vehicle (UAV) propellers during hovering flight. The tests have been conducted on [Formula: see text] ultralight carbon fiber propellers using a bespoke mount and the RCBenchmark Series 1780 dynamometer at various degrees of overlap [Formula: see text] and vertical separation [Formula: see text]. A great deal of confusion regarding the losses that are associated with mounting propellers in a co-axial configuration is reported in the literature, with a summary of historical tandem helicopters having been conducted. The results highlight a region of beneficial overlap (0–20%), which has the potential to be advantageous to a wide range of UAVs.","PeriodicalId":164619,"journal":{"name":"Unmanned Syst.","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117295461","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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