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Prof. Domenico Accardo
DII—Department of Industrial Engineering, University of Naples Federico II, Piazzale Vincenzo Tecchio, 80, Naples, Italy

Basic Info


Research Keywords & Expertise

0 Air Traffic Management
0 Autonomous Vehicles
0 Data Fusion
0 Integrated Navigation Systems
0 Unmanned traffic management

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Collision avoidance
Sense and avoid
Data Fusion
Integrated Navigation Systems
Unmanned traffic management
Autonomous Vehicles
Mems inertial sensors
Air Traffic Management

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Journal article
Published: 16 July 2021 in Sensors
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The paper deals with performance enhancement of low-cost, consumer-grade inertial sensors realized by means of Micro Electro-Mechanical Systems (MEMS) technology. Focusing their attention on the reduction of bias instability and random walk-driven drift of cost-effective MEMS accelerometers and gyroscopes, the authors hereinafter propose a suitable method, based on a redundant configuration and complemented with a proper measurement procedure, to improve the performance of low-cost, consumer-grade MEMS sensors. The performance of the method is assessed by means of an adequate prototype and compared with that assured by a commercial, expensive, tactical-grade MEMS inertial measurement unit, taken as reference. Obtained results highlight the promising reliability and efficacy of the method in estimating position, velocity, and attitude of vehicles; in particular, bias instability and random walk reduction greater than 25% is, in fact, experienced. Moreover, differences as low as 0.025 rad and 0.89 m are obtained when comparing position and attitude estimates provided by the prototype and those granted by the tactical-grade MEMS IMU.

ACS Style

Giorgio de Alteriis; Domenico Accardo; Claudia Conte; Rosario Schiano Lo Moriello. Performance Enhancement of Consumer-Grade MEMS Sensors through Geometrical Redundancy. Sensors 2021, 21, 4851 .

AMA Style

Giorgio de Alteriis, Domenico Accardo, Claudia Conte, Rosario Schiano Lo Moriello. Performance Enhancement of Consumer-Grade MEMS Sensors through Geometrical Redundancy. Sensors. 2021; 21 (14):4851.

Chicago/Turabian Style

Giorgio de Alteriis; Domenico Accardo; Claudia Conte; Rosario Schiano Lo Moriello. 2021. "Performance Enhancement of Consumer-Grade MEMS Sensors through Geometrical Redundancy." Sensors 21, no. 14: 4851.

Journal article
Published: 16 July 2021 in Drones
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This paper presents a method developed to predict the flight-time employed by a drone to complete a planned path adopting a machine-learning-based approach. A generic path is cut in properly designed corner-shaped standard sub-paths and the flight-time needed to travel along a standard sub-path is predicted employing a properly trained neural network. The final flight-time over the complete path is computed summing the partial results related to the standard sub-paths. Real drone flight-tests were performed in order to realize an adequate database needed to train the adopted neural network as a classifier, employing the Bayesian regularization backpropagation algorithm as training function. For the network, the relative angle between two sides of a corner and the wind condition are the inputs, while the flight-time over the corner is the output parameter. Then, generic paths were designed and performed to test the method. The total flight-time as resulting from the drone telemetry was compared with the flight-time predicted by the developed method based on machine learning techniques. At the end of the paper, the proposed method was demonstrated as effective in predicting possible collisions among drones flying intersecting paths, as a possible application to support the development of unmanned traffic management procedures.

ACS Style

Claudia Conte; Giorgio de Alteriis; Rosario Schiano Lo Moriello; Domenico Accardo; Giancarlo Rufino. Drone Trajectory Segmentation for Real-Time and Adaptive Time-Of-Flight Prediction. Drones 2021, 5, 62 .

AMA Style

Claudia Conte, Giorgio de Alteriis, Rosario Schiano Lo Moriello, Domenico Accardo, Giancarlo Rufino. Drone Trajectory Segmentation for Real-Time and Adaptive Time-Of-Flight Prediction. Drones. 2021; 5 (3):62.

Chicago/Turabian Style

Claudia Conte; Giorgio de Alteriis; Rosario Schiano Lo Moriello; Domenico Accardo; Giancarlo Rufino. 2021. "Drone Trajectory Segmentation for Real-Time and Adaptive Time-Of-Flight Prediction." Drones 5, no. 3: 62.

Conference paper
Published: 06 January 2019 in AIAA Scitech 2019 Forum
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ACS Style

Rita Fontanella; Giorgio de Alteriis; Rosario Schiano Lo Moriello; Domenico Accardo; Leopoldo Angrisani. Results of Field testing for an Integrated GPS/INS Unit based on Low-cost Redundant MEMS Sensors. AIAA Scitech 2019 Forum 2019, 1 .

AMA Style

Rita Fontanella, Giorgio de Alteriis, Rosario Schiano Lo Moriello, Domenico Accardo, Leopoldo Angrisani. Results of Field testing for an Integrated GPS/INS Unit based on Low-cost Redundant MEMS Sensors. AIAA Scitech 2019 Forum. 2019; ():1.

Chicago/Turabian Style

Rita Fontanella; Giorgio de Alteriis; Rosario Schiano Lo Moriello; Domenico Accardo; Leopoldo Angrisani. 2019. "Results of Field testing for an Integrated GPS/INS Unit based on Low-cost Redundant MEMS Sensors." AIAA Scitech 2019 Forum , no. : 1.

Journal article
Published: 29 December 2018 in Safety Science
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Feasibility studies for airport facilities require quantitative assessment of the effects of the routine operations on the area surrounding the planned installation. In some countries such analyses are mandatory and the targets for which the effects need to be evaluated often include: cultural heritage, natural habitat, as well as human comfort and health. Regarding the latter issue, of main concern is the fatality risk due to airport traffic, primarily considering accidents due to landing and take-off operations. Accidents leading to crash may include fuel fires and explosions, but also trigger domino effects such as industrial accidents, possibly amplifying adverse consequences. Quantitative risk analysis for airport facilities is the topic of the study presented, where a probabilistic framework to evaluate the annual fatality risk for airports and surrounding areas is discussed. The risk metric is the individual risk (IR), and the methodology contemplates the tools and procedures to compute the annual expected number of accidents that result in fatality for each point in the area surrounding the airport. Three causes contribute to the evaluation of IR: (i) direct aircraft impact, (ii) heat radiation produced by the burning of fuel possibly released in the crash; (iii) heat radiation or intoxication because the crash involves industrial facilities storing or treating relevant amounts of hazardous materials. The risk analysis requires competencies mainly from three fields: (a) stochastic modelling for uncertainty management and probabilistic evaluation; (b) aeronautical engineering for the modeling of aircraft operations and dynamics that may result in an accident and, finally, (c) chemical engineering for the combustion modeling and for the analysis of cascading effects on industrial targets (also called domino in the following), as well as for the evaluation of health consequences. The developed method is thoroughly discussed in the paper and applied to the foreseen upgrade of the Florence (Italy) airport Amerigo Vespucci, which shows its potential effectiveness in decision making preparatory to airports’ design.

ACS Style

Iunio Iervolino; Domenico Accardo; Anna Elena Tirri; Gianmaria Pio; Ernesto Salzano. Quantitative risk analysis for the Amerigo Vespucci (Florence, Italy) airport including domino effects. Safety Science 2018, 113, 472 -489.

AMA Style

Iunio Iervolino, Domenico Accardo, Anna Elena Tirri, Gianmaria Pio, Ernesto Salzano. Quantitative risk analysis for the Amerigo Vespucci (Florence, Italy) airport including domino effects. Safety Science. 2018; 113 ():472-489.

Chicago/Turabian Style

Iunio Iervolino; Domenico Accardo; Anna Elena Tirri; Gianmaria Pio; Ernesto Salzano. 2018. "Quantitative risk analysis for the Amerigo Vespucci (Florence, Italy) airport including domino effects." Safety Science 113, no. : 472-489.

Journal article
Published: 22 November 2018 in Aerospace Science and Technology
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This paper presents a cooperative navigation approach for Unmanned Aerial Vehicles (UAVs) that allows robust and accurate attitude determination for a chief vehicle flying in formation with other deputy UAVs. The proposed method is based on a tightly coupled Extended Kalman Filter (EKF) that exploits the spatial diversity of measurements coming from Global Navigation Satellite Systems (GNSS) receivers and a vision system, which are integrated with inertial and magnetic sensor data. The focus is set on outdoor environments and the innovative idea is to extend attitude estimation approaches based on multiple GNSS antennas, to a multi-vehicle system where differential-GNSS and vision-based UAV-to-UAV tracking are exploited to build a virtual additional navigation sensor. Concept and processing architecture are described with emphasis on the EKF measurement update phase which is applicable for any number of cooperating deputies, and for different GNSS processing architectures. Performance of the proposed method is assessed through experimental tests involving two multi-rotors and two fixed ground antennas, one of which is used as Ground Control Point for pointing accuracy analysis. Results show the potential of the developed approach in terms of accuracy and capability to provide drift-free estimates, in real time or in post processing scenarios.

ACS Style

Amedeo Rodi Vetrella; Giancarmine Fasano; Domenico Accardo. Attitude estimation for cooperating UAVs based on tight integration of GNSS and vision measurements. Aerospace Science and Technology 2018, 84, 966 -979.

AMA Style

Amedeo Rodi Vetrella, Giancarmine Fasano, Domenico Accardo. Attitude estimation for cooperating UAVs based on tight integration of GNSS and vision measurements. Aerospace Science and Technology. 2018; 84 ():966-979.

Chicago/Turabian Style

Amedeo Rodi Vetrella; Giancarmine Fasano; Domenico Accardo. 2018. "Attitude estimation for cooperating UAVs based on tight integration of GNSS and vision measurements." Aerospace Science and Technology 84, no. : 966-979.

Journal article
Published: 10 October 2018 in Sensors
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This paper presents a visual-based approach that allows an Unmanned Aerial Vehicle (UAV) to detect and track a cooperative flying vehicle autonomously using a monocular camera. The algorithms are based on template matching and morphological filtering, thus being able to operate within a wide range of relative distances (i.e., from a few meters up to several tens of meters), while ensuring robustness against variations of illumination conditions, target scale and background. Furthermore, the image processing chain takes full advantage of navigation hints (i.e., relative positioning and own-ship attitude estimates) to improve the computational efficiency and optimize the trade-off between correct detections, false alarms and missed detections. Clearly, the required exchange of information is enabled by the cooperative nature of the formation through a reliable inter-vehicle data-link. Performance assessment is carried out by exploiting flight data collected during an ad hoc experimental campaign. The proposed approach is a key building block of cooperative architectures designed to improve UAV navigation performance either under nominal GNSS coverage or in GNSS-challenging environments.

ACS Style

Roberto Opromolla; Giancarmine Fasano; Domenico Accardo. A Vision-Based Approach to UAV Detection and Tracking in Cooperative Applications. Sensors 2018, 18, 3391 .

AMA Style

Roberto Opromolla, Giancarmine Fasano, Domenico Accardo. A Vision-Based Approach to UAV Detection and Tracking in Cooperative Applications. Sensors. 2018; 18 (10):3391.

Chicago/Turabian Style

Roberto Opromolla; Giancarmine Fasano; Domenico Accardo. 2018. "A Vision-Based Approach to UAV Detection and Tracking in Cooperative Applications." Sensors 18, no. 10: 3391.

Conference paper
Published: 01 September 2018 in 2018 IEEE/AIAA 37th Digital Avionics Systems Conference (DASC)
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This paper presents an overview and a performance analysis of sensing approaches aimed at providing small Unmanned Aircraft Systems (UAS) flying in the low altitude airspace with sense and avoid capabilities. Limited weight, size and power resources represent significant challenges especially considering non-cooperative architectures and avoidance of flying obstacles. An analysis of conflict detection performance levels achievable exploiting different sensing architectures, i.e., based on (compact) radar, LIDAR, cameras and multi-sensor systems, is carried out by means of numerical simulations in which 2D frontal collision scenarios are reproduced. Also, an experimental campaign is planned, aimed to test sense and avoid technologies and algorithms using flight data collected by a fleet of small fixed-/rotary-wing UAS. First analyses regarding the performance of non-cooperative vision-based detection and tracking algorithms in a small UAS scenario are finally presented.

ACS Style

Roberto Opromolla; Giancarmine Fasano; Domenico Accardo. Perspectives and Sensing Concepts for Small UAS Sense and Avoid. 2018 IEEE/AIAA 37th Digital Avionics Systems Conference (DASC) 2018, 1 -10.

AMA Style

Roberto Opromolla, Giancarmine Fasano, Domenico Accardo. Perspectives and Sensing Concepts for Small UAS Sense and Avoid. 2018 IEEE/AIAA 37th Digital Avionics Systems Conference (DASC). 2018; ():1-10.

Chicago/Turabian Style

Roberto Opromolla; Giancarmine Fasano; Domenico Accardo. 2018. "Perspectives and Sensing Concepts for Small UAS Sense and Avoid." 2018 IEEE/AIAA 37th Digital Avionics Systems Conference (DASC) , no. : 1-10.

Journal article
Published: 10 May 2018 in Sensors and Actuators A: Physical
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In this paper, the application of Artificial Neural Networks to perform the thermal calibration of bias for Micro Electro-Mechanical gyros that are installed in Inertial Measurement Units is discussed. In recent years, the interest in using these systems to perform integrated inertial navigation has increased. Several new applications, related to the use of autonomous systems and personal navigation systems in GPS-challenging environments, have been developed. Thermal calibration of bias is a key issue to be assessed to achieve the best performance of a Micro Electro-Mechanical gyro. It can reduce sensor bias to one order of magnitude lower than non-calibrated conditions. Usually, thermal calibration is performed by exploiting polynomial fitting, i.e. finding the least-square polynomial that fits experimental data collected during laboratory tests in a climatic chamber. Polynomials have some drawbacks when they are applied to Micro Electro-Mechanical gyro calibration. They are not adequate to model abrupt change of bias trend in small temperature intervals and sensor hysteresis. For this reason, in the present paper, the use of Back Propagation Artificial Neural Networks is suggested as an improvement of polynomial fitting. Indeed, Neural Networks have intrinsic adaptive configurations and standard training and testing techniques, so that they can be adequately adopted for mapping thermal bias variations. In this paper, the polynomial fitting and Neural Network compensation algorithms are compared on selected testing points where the two techniques have the largest difference. Results highlight that the proposed method has better performance on these points. Therefore, the time in which the flight attitude accuracy meets the requirements imposed by the current regulations is improved by 20%.

ACS Style

Rita Fontanella; Domenico Accardo; Rosario Schiano Lo Moriello; Leopoldo Angrisani; Domenico De Simone. MEMS gyros temperature calibration through artificial neural networks. Sensors and Actuators A: Physical 2018, 279, 553 -565.

AMA Style

Rita Fontanella, Domenico Accardo, Rosario Schiano Lo Moriello, Leopoldo Angrisani, Domenico De Simone. MEMS gyros temperature calibration through artificial neural networks. Sensors and Actuators A: Physical. 2018; 279 ():553-565.

Chicago/Turabian Style

Rita Fontanella; Domenico Accardo; Rosario Schiano Lo Moriello; Leopoldo Angrisani; Domenico De Simone. 2018. "MEMS gyros temperature calibration through artificial neural networks." Sensors and Actuators A: Physical 279, no. : 553-565.

Journal article
Published: 07 May 2018 in Sensors
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This paper presents an innovative model for integrating thermal compensation of gyro bias error into an augmented state Kalman filter. The developed model is applied in the Zero Velocity Update filter for inertial units manufactured by exploiting Micro Electro-Mechanical System (MEMS) gyros. It is used to remove residual bias at startup. It is a more effective alternative to traditional approach that is realized by cascading bias thermal correction by calibration and traditional Kalman filtering for bias tracking. This function is very useful when adopted gyros are manufactured using MEMS technology. These systems have significant limitations in terms of sensitivity to environmental conditions. They are characterized by a strong correlation of the systematic error with temperature variations. The traditional process is divided into two separated algorithms, i.e., calibration and filtering, and this aspect reduces system accuracy, reliability, and maintainability. This paper proposes an innovative Zero Velocity Update filter that just requires raw uncalibrated gyro data as input. It unifies in a single algorithm the two steps from the traditional approach. Therefore, it saves time and economic resources, simplifying the management of thermal correction process. In the paper, traditional and innovative Zero Velocity Update filters are described in detail, as well as the experimental data set used to test both methods. The performance of the two filters is compared both in nominal conditions and in the typical case of a residual initial alignment bias. In this last condition, the innovative solution shows significant improvements with respect to the traditional approach. This is the typical case of an aircraft or a car in parking conditions under solar input.

ACS Style

Rita Fontanella; Domenico Accardo; Rosario Schiano Lo Moriello; Leopoldo Angrisani; Domenico De Simone. An Innovative Strategy for Accurate Thermal Compensation of Gyro Bias in Inertial Units by Exploiting a Novel Augmented Kalman Filter. Sensors 2018, 18, 1457 .

AMA Style

Rita Fontanella, Domenico Accardo, Rosario Schiano Lo Moriello, Leopoldo Angrisani, Domenico De Simone. An Innovative Strategy for Accurate Thermal Compensation of Gyro Bias in Inertial Units by Exploiting a Novel Augmented Kalman Filter. Sensors. 2018; 18 (5):1457.

Chicago/Turabian Style

Rita Fontanella; Domenico Accardo; Rosario Schiano Lo Moriello; Leopoldo Angrisani; Domenico De Simone. 2018. "An Innovative Strategy for Accurate Thermal Compensation of Gyro Bias in Inertial Units by Exploiting a Novel Augmented Kalman Filter." Sensors 18, no. 5: 1457.

Article
Published: 23 April 2018 in Journal of Intelligent & Robotic Systems
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This paper presents a cooperative navigation technique which exploits relative vision-based sensing and carrier-phase differential GPS (CDGPS) among antennas embarked on different flying platforms, to provide accurate UAV attitude estimates in real time or in post-processing phase. It is assumed that all UAVs are under nominal GPS coverage. The logical architecture and the main algorithmic steps are highlighted, and the adopted CDGPS processing strategy is described. The experimental setup used to evaluate the proposed approach comprises two multi-rotors and two ground antennas, one of which is used as a benchmark for attitude accuracy estimation. Results from flight tests are presented in which the attitude solution obtained by integrating CDGPS and vision (CDGPS/Vision) measurements within and Extended Kalman Filter is compared with estimates provided by the onboard navigation system and with the results of a formerly developed code-based differential GPS (DGPS/Vision) approach. Benchmark-based analyses confirm that CDGPS/Vision approach outperforms both onboard navigation system and DGPS/Vision approach.

ACS Style

Amedeo Rodi Vetrella; Flavia Causa; Alfredo Renga; Giancarmine Fasano; Domenico Accardo; Michele Grassi. Multi-UAV Carrier Phase Differential GPS and Vision-based Sensing for High Accuracy Attitude Estimation. Journal of Intelligent & Robotic Systems 2018, 93, 245 -260.

AMA Style

Amedeo Rodi Vetrella, Flavia Causa, Alfredo Renga, Giancarmine Fasano, Domenico Accardo, Michele Grassi. Multi-UAV Carrier Phase Differential GPS and Vision-based Sensing for High Accuracy Attitude Estimation. Journal of Intelligent & Robotic Systems. 2018; 93 (1-2):245-260.

Chicago/Turabian Style

Amedeo Rodi Vetrella; Flavia Causa; Alfredo Renga; Giancarmine Fasano; Domenico Accardo; Michele Grassi. 2018. "Multi-UAV Carrier Phase Differential GPS and Vision-based Sensing for High Accuracy Attitude Estimation." Journal of Intelligent & Robotic Systems 93, no. 1-2: 245-260.

Conference paper
Published: 07 January 2018 in 2018 AIAA Information Systems-AIAA Infotech @ Aerospace
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ACS Style

Rita Fontanella; Francesco Buonavolontà; Rosario Schiano Lo Moriello; Domenico Accardo; Leopoldo Angrisani. Exploiting Low-Cost Compact Sensor Configurations Performance by Redundancy. 2018 AIAA Information Systems-AIAA Infotech @ Aerospace 2018, 1 .

AMA Style

Rita Fontanella, Francesco Buonavolontà, Rosario Schiano Lo Moriello, Domenico Accardo, Leopoldo Angrisani. Exploiting Low-Cost Compact Sensor Configurations Performance by Redundancy. 2018 AIAA Information Systems-AIAA Infotech @ Aerospace. 2018; ():1.

Chicago/Turabian Style

Rita Fontanella; Francesco Buonavolontà; Rosario Schiano Lo Moriello; Domenico Accardo; Leopoldo Angrisani. 2018. "Exploiting Low-Cost Compact Sensor Configurations Performance by Redundancy." 2018 AIAA Information Systems-AIAA Infotech @ Aerospace , no. : 1.

Conference paper
Published: 07 January 2018 in 2018 AIAA Information Systems-AIAA Infotech @ Aerospace
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ACS Style

Roberto Opromolla; Amedeo Rodi Vetrella; Giancarmine Fasano; Domenico Accardo. Airborne Visual Tracking for Cooperative UAV Swarms. 2018 AIAA Information Systems-AIAA Infotech @ Aerospace 2018, 1 .

AMA Style

Roberto Opromolla, Amedeo Rodi Vetrella, Giancarmine Fasano, Domenico Accardo. Airborne Visual Tracking for Cooperative UAV Swarms. 2018 AIAA Information Systems-AIAA Infotech @ Aerospace. 2018; ():1.

Chicago/Turabian Style

Roberto Opromolla; Amedeo Rodi Vetrella; Giancarmine Fasano; Domenico Accardo. 2018. "Airborne Visual Tracking for Cooperative UAV Swarms." 2018 AIAA Information Systems-AIAA Infotech @ Aerospace , no. : 1.

Conference paper
Published: 21 November 2017 in International Conference on Space Optics — ICSO 2000
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ACS Style

Domenico Accardo; Giancarlo Rufino. An effective procedure to operate tests of star tracker software routines using a sensor model. International Conference on Space Optics — ICSO 2000 2017, 23 .

AMA Style

Domenico Accardo, Giancarlo Rufino. An effective procedure to operate tests of star tracker software routines using a sensor model. International Conference on Space Optics — ICSO 2000. 2017; ():23.

Chicago/Turabian Style

Domenico Accardo; Giancarlo Rufino. 2017. "An effective procedure to operate tests of star tracker software routines using a sensor model." International Conference on Space Optics — ICSO 2000 , no. : 23.

Conference paper
Published: 03 November 2017 in Experimental Robotics
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In many unmanned aerial vehicle (UAV) applications, flexible trajectory generation algorithms are required to enable high levels of autonomy for critical mission phases, such as take-off, area coverage, and landing. In this paper, we present a guidance approach which uses the improved intrinsic tau guidance theory to create spatio-temporal 4-D trajectories for a desired time-to-contact with a landing platform tracked by a visual sensor. This allows us to perform maneuvers with tunable trajectory profiles, while catering for static or non-static starting and terminating motion states. We validate our method in both simulations and real platform experiments by using rotary-wing UAVs to land on static platforms. Results show that our method achieves smooth landings within 10 cm accuracy, with easily adjustable trajectory parameters.

ACS Style

Amedeo Rodi Vetrella; Inkyu Sa; Marija Popović; Raghav Khanna; Juan Nieto; Giancarmine Fasano; Domenico Accardo; Roland Siegwart. Improved Tau-Guidance and Vision-Aided Navigation for Robust Autonomous Landing of UAVs. Experimental Robotics 2017, 115 -128.

AMA Style

Amedeo Rodi Vetrella, Inkyu Sa, Marija Popović, Raghav Khanna, Juan Nieto, Giancarmine Fasano, Domenico Accardo, Roland Siegwart. Improved Tau-Guidance and Vision-Aided Navigation for Robust Autonomous Landing of UAVs. Experimental Robotics. 2017; ():115-128.

Chicago/Turabian Style

Amedeo Rodi Vetrella; Inkyu Sa; Marija Popović; Raghav Khanna; Juan Nieto; Giancarmine Fasano; Domenico Accardo; Roland Siegwart. 2017. "Improved Tau-Guidance and Vision-Aided Navigation for Robust Autonomous Landing of UAVs." Experimental Robotics , no. : 115-128.

Journal article
Published: 01 June 2017 in Journal of Aerospace Information Systems
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This paper presents a cooperative unmanned aerial vehicle navigation algorithm that allows a chief vehicle (equipped with inertial and magnetic sensors, a Global Positioning System receiver, and a vision system) to improve its navigation performance (in real time or in postprocessing phase), exploiting line-of-sight measurements from formation-flying deputies equipped with Global Positioning System receivers. The key concept is to integrate differential Global Positioning System and visual tracking information within a sensor fusion algorithm based on the extended Kalman filter. The developed concept and processing architecture are described, with a focus on the filtering algorithm. Then, flight-testing strategy and experimental results are presented. In particular, cooperative navigation output is compared with the estimates provided by the onboard autopilot system of a customized quadrotor. The analysis shows the potential of the developed approach, mainly deriving from the possibility to exploit accurate magnetic- and inertial-independent information.

ACS Style

Amedeo Rodi Vetrella; Giancarmine Fasano; Domenico Accardo. Satellite and Vision-Aided Sensor Fusion for Cooperative Navigation of Unmanned Aircraft Swarms. Journal of Aerospace Information Systems 2017, 14, 327 -344.

AMA Style

Amedeo Rodi Vetrella, Giancarmine Fasano, Domenico Accardo. Satellite and Vision-Aided Sensor Fusion for Cooperative Navigation of Unmanned Aircraft Swarms. Journal of Aerospace Information Systems. 2017; 14 (6):327-344.

Chicago/Turabian Style

Amedeo Rodi Vetrella; Giancarmine Fasano; Domenico Accardo. 2017. "Satellite and Vision-Aided Sensor Fusion for Cooperative Navigation of Unmanned Aircraft Swarms." Journal of Aerospace Information Systems 14, no. 6: 327-344.

Conference paper
Published: 01 June 2017 in 2017 5th IEEE International Conference on Models and Technologies for Intelligent Transportation Systems (MT-ITS)
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This paper presents a software application to derive system specifications for drones operating inside the future Unmanned Traffic Management system. It describes a software tool able to support the decision-making process, which is aimed at defining drone configurations that are customized on mission needs while accounting for requirements related to flight authorization. This tool is dedicated to support drone end users to find out the most appropriate configuration for a drone system used to carry out a specific mission. The tool aims at developing a standard approach to find out a suitable solution in terms of equipment to be used and operation framework, also in view of automatic authorization procedures by regulation entities. It can be used in a future intelligent transportation system for drones. The advantage is the reduction of the effort to manage the large number of different drone mission conditions.

ACS Style

Rita Fontanella; Amedeo Rodi Vetrella; Giancarmine Fasano; Domenico Accardo; Rosario Schiano Lo Moriello; Leopoldo Angrisani; Remy Girard. A standardized approach to derive system specifications for drones operating in the future UTM scenario. 2017 5th IEEE International Conference on Models and Technologies for Intelligent Transportation Systems (MT-ITS) 2017, 250 -255.

AMA Style

Rita Fontanella, Amedeo Rodi Vetrella, Giancarmine Fasano, Domenico Accardo, Rosario Schiano Lo Moriello, Leopoldo Angrisani, Remy Girard. A standardized approach to derive system specifications for drones operating in the future UTM scenario. 2017 5th IEEE International Conference on Models and Technologies for Intelligent Transportation Systems (MT-ITS). 2017; ():250-255.

Chicago/Turabian Style

Rita Fontanella; Amedeo Rodi Vetrella; Giancarmine Fasano; Domenico Accardo; Rosario Schiano Lo Moriello; Leopoldo Angrisani; Remy Girard. 2017. "A standardized approach to derive system specifications for drones operating in the future UTM scenario." 2017 5th IEEE International Conference on Models and Technologies for Intelligent Transportation Systems (MT-ITS) , no. : 250-255.

Conference paper
Published: 01 June 2017 in 2017 International Conference on Unmanned Aircraft Systems (ICUAS)
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This paper presents a cooperative navigation technique which exploits relative vision-based sensing and carrier-phase differential GPS (CDGPS) between antennas embarked on different flying platforms, to improve UAV attitude estimation in real time or in post-processing phase. The focus is set on outdoor environments, hence it is assumed that all vehicles are under nominal GPS coverage. The logical architecture and the main processing steps are highlighted with particular focus on the CDGPS processing. The experimental setup used to evaluate the proposed approach comprises two multi-rotors and two ground antennas. Results from flight tests are presented in which both code-based differential GPS (DGPS) and CDGPS solutions are analyzed. In addition, the attitude solution obtained by integrating CDGPS and vision (CDGPS/Vision) is compared with attitude estimates provided by the onboard autopilot system and with those obtained by adopting a DGPS/Vision approach.

ACS Style

Amedeo Rodi Vetrella; Flavia Causa; Alfredo Renga; Giancarmine Fasano; Domenico Accardo; Michele Grassi. Flight demonstration of multi-UAV CDGPS and vision-based sensing for high accuracy attitude estimation. 2017 International Conference on Unmanned Aircraft Systems (ICUAS) 2017, 237 -246.

AMA Style

Amedeo Rodi Vetrella, Flavia Causa, Alfredo Renga, Giancarmine Fasano, Domenico Accardo, Michele Grassi. Flight demonstration of multi-UAV CDGPS and vision-based sensing for high accuracy attitude estimation. 2017 International Conference on Unmanned Aircraft Systems (ICUAS). 2017; ():237-246.

Chicago/Turabian Style

Amedeo Rodi Vetrella; Flavia Causa; Alfredo Renga; Giancarmine Fasano; Domenico Accardo; Michele Grassi. 2017. "Flight demonstration of multi-UAV CDGPS and vision-based sensing for high accuracy attitude estimation." 2017 International Conference on Unmanned Aircraft Systems (ICUAS) , no. : 237-246.

Journal article
Published: 02 March 2017 in Sensors
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The search for undiscovered planets outside the solar system is a scientific topic that is rapidly spreading into the astrophysical and engineering communities. In this framework, the design of an innovative payload to detect exoplanets from a nano-sized space platform, like a 3U cubesat, is presented. The selected detection method is photometric transit, and the payload aims to detect flux decrements down to ~0.01% with a precision of 12 ppm. The payload design is also aimed at false positive recognition. The solution consists of a four-facets pyramid on the top of the payload, to allow for measurement redundancy and low-resolution spectral dispersion of the star images. The innovative concept is the use of a small and cheap platform for a relevant astronomical mission. The faintest observable target star has V-magnitude equal to 3.38. Despite missions aimed at ultra-precise photometry from microsatellites (e.g., MOST, BRITE), the transit of exoplanets orbiting very bright stars has not yet been surveyed photometrically from space, since any observation from a small/medium sized (30 cm optical aperture) telescope would saturate the detector. This cubesat mission can provide these missing measurements. This work is set up as a demonstrative project to verify the feasibility of the payload concept.

ACS Style

Marcella Iuzzolino; Domenico Accardo; Giancarlo Rufino; Ernesto Oliva; Andrea Tozzi; Pietro Schipani. A Cubesat Payload for Exoplanet Detection. Sensors 2017, 17, 493 .

AMA Style

Marcella Iuzzolino, Domenico Accardo, Giancarlo Rufino, Ernesto Oliva, Andrea Tozzi, Pietro Schipani. A Cubesat Payload for Exoplanet Detection. Sensors. 2017; 17 (3):493.

Chicago/Turabian Style

Marcella Iuzzolino; Domenico Accardo; Giancarlo Rufino; Ernesto Oliva; Andrea Tozzi; Pietro Schipani. 2017. "A Cubesat Payload for Exoplanet Detection." Sensors 17, no. 3: 493.

Conference paper
Published: 05 January 2017 in AIAA Information Systems-AIAA Infotech @ Aerospace
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An implementation of a distributed flocking algorithm with obstacle avoidance capability for a swarm of UAVs is presented. Aim of the algorithm is to produce the accelerations to guide the flock in reaching its destination while avoiding obstacles and each other. The distributed nature of the algorithm consists in the capability of each component of the swarm to calculate its own acceleration while having only partial measurements, such as position and velocity, of only neighbouring vehicles. A limitation related to the strong assumptions that have to be made about the obstacles shape has been individuated in literature. The root cause has been identified and a possible solution has been investigated to overcome the restriction

ACS Style

Serena Iovino; Amedeo Rodi Vetrella; Giancarmine Fasano; Domenico Accardo; Al Savvaris. Implementation of a Distributed Flocking Algorithm with Obstacle Avoidance Capability for UAV Swarming. AIAA Information Systems-AIAA Infotech @ Aerospace 2017, 1 .

AMA Style

Serena Iovino, Amedeo Rodi Vetrella, Giancarmine Fasano, Domenico Accardo, Al Savvaris. Implementation of a Distributed Flocking Algorithm with Obstacle Avoidance Capability for UAV Swarming. AIAA Information Systems-AIAA Infotech @ Aerospace. 2017; ():1.

Chicago/Turabian Style

Serena Iovino; Amedeo Rodi Vetrella; Giancarmine Fasano; Domenico Accardo; Al Savvaris. 2017. "Implementation of a Distributed Flocking Algorithm with Obstacle Avoidance Capability for UAV Swarming." AIAA Information Systems-AIAA Infotech @ Aerospace , no. : 1.

Conference paper
Published: 05 January 2017 in AIAA Information Systems-AIAA Infotech @ Aerospace
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ACS Style

Rita Fontanella; Domenico Accardo; Egidio Caricati; Stefano Cimmino; Domenico De Simone; Giovanni Lucignano. Improving Inertial Attitude Measurement Performance by Exploiting MEMS Gyros and Neural Thermal Calibration. AIAA Information Systems-AIAA Infotech @ Aerospace 2017, 1 .

AMA Style

Rita Fontanella, Domenico Accardo, Egidio Caricati, Stefano Cimmino, Domenico De Simone, Giovanni Lucignano. Improving Inertial Attitude Measurement Performance by Exploiting MEMS Gyros and Neural Thermal Calibration. AIAA Information Systems-AIAA Infotech @ Aerospace. 2017; ():1.

Chicago/Turabian Style

Rita Fontanella; Domenico Accardo; Egidio Caricati; Stefano Cimmino; Domenico De Simone; Giovanni Lucignano. 2017. "Improving Inertial Attitude Measurement Performance by Exploiting MEMS Gyros and Neural Thermal Calibration." AIAA Information Systems-AIAA Infotech @ Aerospace , no. : 1.