Pub Date : 2019-11-01DOI: 10.1109/REDUAS47371.2019.8999718
J. Amador, J.R. Martínez de Dios, J. Paneque, A. Ollero
Most existing aerial robotics testbeds have significant set-up and maintenance costs that restrict their use. This paper presents a low-cost multi-drone testbed for agile and safe performing proof-of-concept experiments. It uses low-weight, low-size Crazyflies drones and low-cost lighthouse positioning system for drone pose estimations. Its flexible and modular ROS-based architecture can be used to easily test multi-drone perception, control and planning techniques and can easily integrate bigger drones. The presented testbed does not require a dedicated room and can be set-up in less than one hour. The paper presents the testbed and validates its operation with multi-drone target tracking experiments.
{"title":"An Agile Low-cost Testbed for Multi-Drone Target Tracking","authors":"J. Amador, J.R. Martínez de Dios, J. Paneque, A. Ollero","doi":"10.1109/REDUAS47371.2019.8999718","DOIUrl":"https://doi.org/10.1109/REDUAS47371.2019.8999718","url":null,"abstract":"Most existing aerial robotics testbeds have significant set-up and maintenance costs that restrict their use. This paper presents a low-cost multi-drone testbed for agile and safe performing proof-of-concept experiments. It uses low-weight, low-size Crazyflies drones and low-cost lighthouse positioning system for drone pose estimations. Its flexible and modular ROS-based architecture can be used to easily test multi-drone perception, control and planning techniques and can easily integrate bigger drones. The presented testbed does not require a dedicated room and can be set-up in less than one hour. The paper presents the testbed and validates its operation with multi-drone target tracking experiments.","PeriodicalId":351115,"journal":{"name":"2019 Workshop on Research, Education and Development of Unmanned Aerial Systems (RED UAS)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123289167","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 : 2019-11-01DOI: 10.1109/REDUAS47371.2019.8999694
Yiyun Bai, Ju-Hyeon Hong, A. Zolotas
A novel design of amphibious UAV with a swimming-ring shaped floater that can inflate before landing and deflate after taking off is presented. An air pump system is developed to control the floater and is integrated in the whole flight control system. The mechanism of such system is discussed, while simulations in MATLAB and Simulink carried out for a UAV with simple missions and trajectories are shown. Results illustrate the feasibility of using the proposed design within the remit of water landing UAVs.
{"title":"Development of a Novel Water Landing UAV with Deflatable Floater","authors":"Yiyun Bai, Ju-Hyeon Hong, A. Zolotas","doi":"10.1109/REDUAS47371.2019.8999694","DOIUrl":"https://doi.org/10.1109/REDUAS47371.2019.8999694","url":null,"abstract":"A novel design of amphibious UAV with a swimming-ring shaped floater that can inflate before landing and deflate after taking off is presented. An air pump system is developed to control the floater and is integrated in the whole flight control system. The mechanism of such system is discussed, while simulations in MATLAB and Simulink carried out for a UAV with simple missions and trajectories are shown. Results illustrate the feasibility of using the proposed design within the remit of water landing UAVs.","PeriodicalId":351115,"journal":{"name":"2019 Workshop on Research, Education and Development of Unmanned Aerial Systems (RED UAS)","volume":"67 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134298197","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 : 2019-11-01DOI: 10.1109/REDUAS47371.2019.8999708
Johannes Autenrieb, Natalia Strawa, Hyo-Sang Shin, Ju-Hyeon Hong
This paper presents a multi-agent mission planning and task allocation framework designed to coordinate autonomous aerial vehicles engaged in a competition scenario. The development was a part of an inter-university UAV Swarm competition that was supported by BAE Systems. The proposed centralised system was developed with the main objectives of robustness and scalability. The system consists of a general mission planning module which decomposes the overall mission into identified sub-stages to achieve the overall mission goal. In order to enable autonomous defence actions a dynamic task allocation approach is proposed. The dynamic task allocation is using received information of detected enemies and utilises the information for a further combinatorial optimisation problem. In this work, we discuss the structure of the framework and present results obtained in a high-fidelity simulation environment. Moreover, a comparative study of the performance of three different optimization algorithms for the given combinatorial problem, namely Kuhn-Munkres, Jonker-Volgenant and Gale-Shapley, implemented in the system is included. The results demonstrate that the best allocation result performances, in terms of minimal costs, are obtained with utilising, both Kuhn-Munkres or Jonker-Volgenant methods, while the Gale-Shapley algorithms have benefits in terms of time efficiency for cases in which minimal costs are not the highest priority.
{"title":"A Mission Planning and Task Allocation Framework For Multi-UAV Swarm Coordination","authors":"Johannes Autenrieb, Natalia Strawa, Hyo-Sang Shin, Ju-Hyeon Hong","doi":"10.1109/REDUAS47371.2019.8999708","DOIUrl":"https://doi.org/10.1109/REDUAS47371.2019.8999708","url":null,"abstract":"This paper presents a multi-agent mission planning and task allocation framework designed to coordinate autonomous aerial vehicles engaged in a competition scenario. The development was a part of an inter-university UAV Swarm competition that was supported by BAE Systems. The proposed centralised system was developed with the main objectives of robustness and scalability. The system consists of a general mission planning module which decomposes the overall mission into identified sub-stages to achieve the overall mission goal. In order to enable autonomous defence actions a dynamic task allocation approach is proposed. The dynamic task allocation is using received information of detected enemies and utilises the information for a further combinatorial optimisation problem. In this work, we discuss the structure of the framework and present results obtained in a high-fidelity simulation environment. Moreover, a comparative study of the performance of three different optimization algorithms for the given combinatorial problem, namely Kuhn-Munkres, Jonker-Volgenant and Gale-Shapley, implemented in the system is included. The results demonstrate that the best allocation result performances, in terms of minimal costs, are obtained with utilising, both Kuhn-Munkres or Jonker-Volgenant methods, while the Gale-Shapley algorithms have benefits in terms of time efficiency for cases in which minimal costs are not the highest priority.","PeriodicalId":351115,"journal":{"name":"2019 Workshop on Research, Education and Development of Unmanned Aerial Systems (RED UAS)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132783642","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 : 2019-11-01DOI: 10.1109/REDUAS47371.2019.8999690
J. Stamenkovich, Lakshman Maalolan, C. Patterson
Our ability to ensure software correctness is especially challenged by autonomous systems. In particular, the use of artificial intelligence can cause unpredictable behavior when encountering situations that were not included in the training data. We describe an alternative to static analysis and conventional testing that monitors and enforces formally specified properties describing a system’s physical state. All external inputs and outputs are monitored by multiple parallel automata synthesized from guards specified as linear temporal logic (LTL) formulas capturing application-specific correctness, safety, and liveness properties. Unlike conventional runtime verification, adding guards does not impact application software performance since the monitor automata are implemented in configurable hardware. In order to remove all dependencies on software, input/output controllers and drivers may also be implemented in configurable hardware. A reporting or corrective action may be taken when a guard is triggered. This architecture is consistent with the guidance prescribed in ASTM F3269-17, Methods to Safely Bound Behavior of Unmanned Aircraft Systems Containing Complex Functions. The monitor and input/output subsystem’s minimal and isolated implementations are amenable to model checking since all components are independent finite state machines. Because this approach makes no assumptions about the root cause of deviation from specifications, it can detect and mitigate: malware threats; sensor and network attacks; software bugs; sensor, actuator and communication faults; and inadvertent or malicious operator errors. We demonstrate this approach with rules defining a virtual cage for a commercially available drone.
{"title":"Formal Assurances for Autonomous Systems Without Verifying Application Software","authors":"J. Stamenkovich, Lakshman Maalolan, C. Patterson","doi":"10.1109/REDUAS47371.2019.8999690","DOIUrl":"https://doi.org/10.1109/REDUAS47371.2019.8999690","url":null,"abstract":"Our ability to ensure software correctness is especially challenged by autonomous systems. In particular, the use of artificial intelligence can cause unpredictable behavior when encountering situations that were not included in the training data. We describe an alternative to static analysis and conventional testing that monitors and enforces formally specified properties describing a system’s physical state. All external inputs and outputs are monitored by multiple parallel automata synthesized from guards specified as linear temporal logic (LTL) formulas capturing application-specific correctness, safety, and liveness properties. Unlike conventional runtime verification, adding guards does not impact application software performance since the monitor automata are implemented in configurable hardware. In order to remove all dependencies on software, input/output controllers and drivers may also be implemented in configurable hardware. A reporting or corrective action may be taken when a guard is triggered. This architecture is consistent with the guidance prescribed in ASTM F3269-17, Methods to Safely Bound Behavior of Unmanned Aircraft Systems Containing Complex Functions. The monitor and input/output subsystem’s minimal and isolated implementations are amenable to model checking since all components are independent finite state machines. Because this approach makes no assumptions about the root cause of deviation from specifications, it can detect and mitigate: malware threats; sensor and network attacks; software bugs; sensor, actuator and communication faults; and inadvertent or malicious operator errors. We demonstrate this approach with rules defining a virtual cage for a commercially available drone.","PeriodicalId":351115,"journal":{"name":"2019 Workshop on Research, Education and Development of Unmanned Aerial Systems (RED UAS)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124995792","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 : 2019-11-01DOI: 10.1109/REDUAS47371.2019.8999683
Vinorth Varatharasan, Alice Shuang Shuang Rao, Eric Toutounji, Ju-Hyeon Hong, Hyo-Sang Shin
An onboard target detection, tracking and avoidance system has been developed in this paper, for low-cost UAV flight controllers using AI-Based approaches. The aim of the proposed system is that an ally UAV can either avoid or track an unexpected enemy UAV with a net to protect itself. In this point of view, a simple and robust target detection, tracking and avoidance system is designed. Two open-source tools were used for the aim: a state-of-the-art object detection technique called SSD and an API for MAVLink compatible systems called MAVSDK. The MAVSDK performs velocity control when a UAV is detected so that the manoeuvre is done simply and efficiently. The proposed system was verified with Software in the loop (SITL) and Hardware in the loop (HITL) simulators. The simplicity of this algorithm makes it innovative, and therefore it should be used in future applications needing robust performances with low-cost hardware such as delivery drone applications.
{"title":"Target Detection, Tracking and Avoidance System for Low-cost UAVs using AI-Based Approaches","authors":"Vinorth Varatharasan, Alice Shuang Shuang Rao, Eric Toutounji, Ju-Hyeon Hong, Hyo-Sang Shin","doi":"10.1109/REDUAS47371.2019.8999683","DOIUrl":"https://doi.org/10.1109/REDUAS47371.2019.8999683","url":null,"abstract":"An onboard target detection, tracking and avoidance system has been developed in this paper, for low-cost UAV flight controllers using AI-Based approaches. The aim of the proposed system is that an ally UAV can either avoid or track an unexpected enemy UAV with a net to protect itself. In this point of view, a simple and robust target detection, tracking and avoidance system is designed. Two open-source tools were used for the aim: a state-of-the-art object detection technique called SSD and an API for MAVLink compatible systems called MAVSDK. The MAVSDK performs velocity control when a UAV is detected so that the manoeuvre is done simply and efficiently. The proposed system was verified with Software in the loop (SITL) and Hardware in the loop (HITL) simulators. The simplicity of this algorithm makes it innovative, and therefore it should be used in future applications needing robust performances with low-cost hardware such as delivery drone applications.","PeriodicalId":351115,"journal":{"name":"2019 Workshop on Research, Education and Development of Unmanned Aerial Systems (RED UAS)","volume":"2010 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127350831","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 : 2019-11-01DOI: 10.1109/REDUAS47371.2019.8999675
A. Barišić, Marko Car, S. Bogdan
In this paper a vision-based system for detection, motion tracking and following of Unmanned Aerial Vehicle (UAV) with other UAV (follower) is presented. For detection of an airborne UAV we apply a convolutional neural network YOLO trained on a collected and processed dataset of 10,000 images. The trained network is capable of detecting various multirotor UAVs in indoor, outdoor and simulation environments. Furthermore, detection results are improved with Kalman filter which ensures steady and reliable information about position and velocity of a target UAV. Preserving the target UAV in the field of view (FOV) and at required distance is accomplished by a simple nonlinear controller based on visual servoing strategy. The proposed system achieves a real-time performance on Neural Compute Stick 2 with a speed of 20 frames per second (FPS) for the detection of an UAV. Justification and efficiency of the developed vision-based system are confirmed in Gazebo simulation experiment where the target UAV is executing a 3D trajectory in a shape of number eight.
{"title":"Vision-based system for a real-time detection and following of UAV","authors":"A. Barišić, Marko Car, S. Bogdan","doi":"10.1109/REDUAS47371.2019.8999675","DOIUrl":"https://doi.org/10.1109/REDUAS47371.2019.8999675","url":null,"abstract":"In this paper a vision-based system for detection, motion tracking and following of Unmanned Aerial Vehicle (UAV) with other UAV (follower) is presented. For detection of an airborne UAV we apply a convolutional neural network YOLO trained on a collected and processed dataset of 10,000 images. The trained network is capable of detecting various multirotor UAVs in indoor, outdoor and simulation environments. Furthermore, detection results are improved with Kalman filter which ensures steady and reliable information about position and velocity of a target UAV. Preserving the target UAV in the field of view (FOV) and at required distance is accomplished by a simple nonlinear controller based on visual servoing strategy. The proposed system achieves a real-time performance on Neural Compute Stick 2 with a speed of 20 frames per second (FPS) for the detection of an UAV. Justification and efficiency of the developed vision-based system are confirmed in Gazebo simulation experiment where the target UAV is executing a 3D trajectory in a shape of number eight.","PeriodicalId":351115,"journal":{"name":"2019 Workshop on Research, Education and Development of Unmanned Aerial Systems (RED UAS)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130557389","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 : 2019-11-01DOI: 10.1109/REDUAS47371.2019.8999677
Siddharth Patel, Andriy Sarabakha, Dogan Kircali, Giuseppe Loianno, E. Kayacan
In this work, we address fast and agile manoeuvre control problem of unmanned aerial vehicles (UAVs) using an artificial neural network (ANN)-assisted conventional controller. Whereas the need for having almost perfect control accuracy for UAVs pushes the operation to boundaries of the performance envelope, safety and reliability concerns enforce researchers to be more conservative in tuning their controllers. As an alternative solution to the aforementioned trade-off, a reliable yet accurate controller is designed for the trajectory tracking of UAVs by learning system dynamics online over the trajectory. What is more, the proposed online learning mechanism helps us to deal with unmodelled dynamics and operational uncertainties. Experimental results validate the proposed approach and show the superiority of our method compared to the conventional controller for fast and agile manoeuvres, at speeds as high as 20m/s. An onboard implementation of the sliding mode control theory-based adaptation rules for the training of the proposed ANN is computationally efficient which allows us to learn system dynamics and operational variations instantly using a low-cost and low-power computer.
{"title":"Artificial Neural Network-Assisted Controller for Fast and Agile UAV Flight: Onboard Implementation and Experimental Results","authors":"Siddharth Patel, Andriy Sarabakha, Dogan Kircali, Giuseppe Loianno, E. Kayacan","doi":"10.1109/REDUAS47371.2019.8999677","DOIUrl":"https://doi.org/10.1109/REDUAS47371.2019.8999677","url":null,"abstract":"In this work, we address fast and agile manoeuvre control problem of unmanned aerial vehicles (UAVs) using an artificial neural network (ANN)-assisted conventional controller. Whereas the need for having almost perfect control accuracy for UAVs pushes the operation to boundaries of the performance envelope, safety and reliability concerns enforce researchers to be more conservative in tuning their controllers. As an alternative solution to the aforementioned trade-off, a reliable yet accurate controller is designed for the trajectory tracking of UAVs by learning system dynamics online over the trajectory. What is more, the proposed online learning mechanism helps us to deal with unmodelled dynamics and operational uncertainties. Experimental results validate the proposed approach and show the superiority of our method compared to the conventional controller for fast and agile manoeuvres, at speeds as high as 20m/s. An onboard implementation of the sliding mode control theory-based adaptation rules for the training of the proposed ANN is computationally efficient which allows us to learn system dynamics and operational variations instantly using a low-cost and low-power computer.","PeriodicalId":351115,"journal":{"name":"2019 Workshop on Research, Education and Development of Unmanned Aerial Systems (RED UAS)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134602185","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 : 2019-11-01DOI: 10.1109/REDUAS47371.2019.8999693
J. Sharples, G. Hattenberger
The French Civil Aviation University’s (ENAC, École Nationale de l’Aviation Civile) main objectives are to train personnel specialised in air transport, and to help these specialists adapt to civil aviation’s evolution, such as the advent of Unmanned Air Systems (UAS) in our skies. This paper shows that in ENAC, education in UAS is carried out in the same way than education in manned aviation topics. The training is divided in main subjects, which are then allocated to each student population according to their future roles: engineers, air traffic controllers, technicians, etc. Teaching is led by skilled personnel and backed up by modern facilities and equipment. This allows ENAC to provide a competent, specialised work force, ready to work on all aspects of the emerging and disruptive UAS-based operations.
法国民航大学(ENAC， École Nationale de l 'Aviation Civil)的主要目标是培养专门从事航空运输的人员，并帮助这些专家适应民用航空的发展，例如我们天空中无人驾驶航空系统(UAS)的出现。本文表明，在ENAC中，UAS教育的开展方式与载人航空主题教育相同。培训分为主要科目，然后根据他们未来的角色分配给每个学生群体:工程师、空中交通管制员、技术人员等。教学由技术人员领导，并以现代化的设施和设备为后盾。这使得ENAC能够提供一支有能力的专业工作队伍，随时准备在新兴的和破坏性的基于无人机的操作的各个方面工作。
{"title":"UAS Education at the French Civil Aviation University","authors":"J. Sharples, G. Hattenberger","doi":"10.1109/REDUAS47371.2019.8999693","DOIUrl":"https://doi.org/10.1109/REDUAS47371.2019.8999693","url":null,"abstract":"The French Civil Aviation University’s (ENAC, École Nationale de l’Aviation Civile) main objectives are to train personnel specialised in air transport, and to help these specialists adapt to civil aviation’s evolution, such as the advent of Unmanned Air Systems (UAS) in our skies. This paper shows that in ENAC, education in UAS is carried out in the same way than education in manned aviation topics. The training is divided in main subjects, which are then allocated to each student population according to their future roles: engineers, air traffic controllers, technicians, etc. Teaching is led by skilled personnel and backed up by modern facilities and equipment. This allows ENAC to provide a competent, specialised work force, ready to work on all aspects of the emerging and disruptive UAS-based operations.","PeriodicalId":351115,"journal":{"name":"2019 Workshop on Research, Education and Development of Unmanned Aerial Systems (RED UAS)","volume":"40 7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116274899","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 : 2019-11-01DOI: 10.1109/REDUAS47371.2019.8999670
Kresimir Turkovic, Marko Car, Mark Orsag
This paper presents a detailed description of the end-effector force estimation of a robotic manipulator attached to an unmanned aerial vehicle. In order to estimate the force, it is assumed that there is a link between the force acting on the end-effector and the change of the torques in the joints of the manipulator in relation to the unloaded manipulator. This link was presented with Newton-Euler’s dynamic model and the Jacobian matrix of the manipulator. The force estimation was tested and validated on several experiments of a manipulator mounted on the aerial vehicle.
{"title":"End-effector force estimation method for an unmanned aerial manipulator","authors":"Kresimir Turkovic, Marko Car, Mark Orsag","doi":"10.1109/REDUAS47371.2019.8999670","DOIUrl":"https://doi.org/10.1109/REDUAS47371.2019.8999670","url":null,"abstract":"This paper presents a detailed description of the end-effector force estimation of a robotic manipulator attached to an unmanned aerial vehicle. In order to estimate the force, it is assumed that there is a link between the force acting on the end-effector and the change of the torques in the joints of the manipulator in relation to the unloaded manipulator. This link was presented with Newton-Euler’s dynamic model and the Jacobian matrix of the manipulator. The force estimation was tested and validated on several experiments of a manipulator mounted on the aerial vehicle.","PeriodicalId":351115,"journal":{"name":"2019 Workshop on Research, Education and Development of Unmanned Aerial Systems (RED UAS)","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122105544","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 : 2019-11-01DOI: 10.1109/REDUAS47371.2019.8999725
H. Fretes, M. Gomez-Redondo, E. Paiva, J. Rodas, R. Gregor
One problem in 3D reconstruction from aerial photographs is the evaluation of the point clouds quality. For point clouds, in general, different authors evaluate their results in different ways. This paper analyzes the existing evaluation methods for the point cloud quality and a new discussion regarding their applicability to aerial photographs is opened. Some of these methods are chosen based on practical issues and applied to a pair of reconstructions. The principal conclusion is that objective methods are the most interesting in photogrammetry applications, particularly the comparison between two point clouds.
{"title":"A Review of Existing Evaluation Methods for Point Clouds Quality","authors":"H. Fretes, M. Gomez-Redondo, E. Paiva, J. Rodas, R. Gregor","doi":"10.1109/REDUAS47371.2019.8999725","DOIUrl":"https://doi.org/10.1109/REDUAS47371.2019.8999725","url":null,"abstract":"One problem in 3D reconstruction from aerial photographs is the evaluation of the point clouds quality. For point clouds, in general, different authors evaluate their results in different ways. This paper analyzes the existing evaluation methods for the point cloud quality and a new discussion regarding their applicability to aerial photographs is opened. Some of these methods are chosen based on practical issues and applied to a pair of reconstructions. The principal conclusion is that objective methods are the most interesting in photogrammetry applications, particularly the comparison between two point clouds.","PeriodicalId":351115,"journal":{"name":"2019 Workshop on Research, Education and Development of Unmanned Aerial Systems (RED UAS)","volume":"9 5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126146376","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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