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The problem of real-time optimal guidance is extremely important for successful autonomous missions. In this paper, the last phases of autonomous lunar landing trajectories are addressed. The proposed guidance is based on the Particle Swarm Optimization, and the differential flatness approach, which is a subclass of the inverse dynamics technique. The trajectory is approximated by polynomials and the control policy is obtained in an analytical closed form solution, where boundary and dynamical constraints are a priori satisfied. Although this procedure leads to sub-optimal solutions, it results in beng fast and thus potentially suitable to be used for real-time purposes. Moreover, the presence of craters on the lunar terrain is considered; therefore, hazard detection and avoidance are also carried out. The proposed guidance is tested by Monte Carlo simulations to evaluate its performances and a robust procedure, made up of safe additional maneuvers, is introduced to counteract optimization failures and achieve soft landing. Finally, the whole procedure is tested through an experimental facility, consisting of a robotic manipulator, equipped with a camera, and a simulated lunar terrain. The results show the efficiency and reliability of the proposed guidance and its possible use for real-time sub-optimal trajectory generation within laboratory applications.
Andrea D’Ambrosio; Andrea Carbone; Dario Spiller; Fabio Curti. PSO-Based Soft Lunar Landing with Hazard Avoidance: Analysis and Experimentation. Aerospace 2021, 8, 195 .
AMA StyleAndrea D’Ambrosio, Andrea Carbone, Dario Spiller, Fabio Curti. PSO-Based Soft Lunar Landing with Hazard Avoidance: Analysis and Experimentation. Aerospace. 2021; 8 (7):195.
Chicago/Turabian StyleAndrea D’Ambrosio; Andrea Carbone; Dario Spiller; Fabio Curti. 2021. "PSO-Based Soft Lunar Landing with Hazard Avoidance: Analysis and Experimentation." Aerospace 8, no. 7: 195.
The development of fast and reliable optimization algorithms is required in order to obtain real-time optimal trajectory on-board spacecraft. In addition, the wide spread of small satellites, due to their low costs, is leading to a greater number of satellite formations in space. This paper presents an Improved version of the Magnetic Charged System Search (IMCSS) metaheuristic algorithm to compute time-suboptimal manoeuvres for satellite formation flying. The proposed algorithm exploits some strategies aimed at improving the convergence to the optimum, such as the chaotic local search and the boundary handling technique, and it is able to self-tune its internal parameters and coefficients. Moreover, the inverse dynamics technique and the differential flatness approach, through the B-splines curves, are used to approximate the trajectory. The optimization procedure is applied to the circular J2 relative model developed by Schweighart and Sedwick and to the elliptical relative motion model developed by Yamanaka and Ankersen. The results of this paper show that the convergence is better achieved by using the proposed tools, thus proving the efficiency and reliability of the algorithm in solving some space engineering problems.
Andrea D’Ambrosio; Dario Spiller; Fabio Curti. Time suboptimal formation flying manoeuvres through improved magnetic charged system search. Advances in Space Research 2021, 67, 3462 -3477.
AMA StyleAndrea D’Ambrosio, Dario Spiller, Fabio Curti. Time suboptimal formation flying manoeuvres through improved magnetic charged system search. Advances in Space Research. 2021; 67 (11):3462-3477.
Chicago/Turabian StyleAndrea D’Ambrosio; Dario Spiller; Fabio Curti. 2021. "Time suboptimal formation flying manoeuvres through improved magnetic charged system search." Advances in Space Research 67, no. 11: 3462-3477.
In this work, we introduce Pontryagin Neural Networks (PoNNs) and employ them to learn the optimal control actions for unconstrained and constrained optimal intercept problems. PoNNs represent a particular family of Physics-Informed Neural Networks (PINNs) specifically designed for tackling optimal control problems via the Pontryagin Minimum Principle (PMP) application (e.g., indirect method). The PMP provides first-order necessary optimality conditions, which result in a Two-Point Boundary Value Problem (TPBVP). More precisely, PoNNs learn the optimal control actions from the unknown solutions of the arising TPBVP, modeling them with Neural Networks (NNs). The characteristic feature of PoNNs is the use of PINNs combined with a functional interpolation technique, named the Theory of Functional Connections (TFC), which forms the so-called PINN-TFC based frameworks. According to these frameworks, the unknown solutions are modeled via the TFC’s constrained expressions using NNs as free functions. The results show that PoNNs can be successfully applied to learn optimal controls for the class of optimal intercept problems considered in this paper.
Andrea D’Ambrosio; Enrico Schiassi; Fabio Curti; Roberto Furfaro. Pontryagin Neural Networks with Functional Interpolation for Optimal Intercept Problems. Mathematics 2021, 9, 996 .
AMA StyleAndrea D’Ambrosio, Enrico Schiassi, Fabio Curti, Roberto Furfaro. Pontryagin Neural Networks with Functional Interpolation for Optimal Intercept Problems. Mathematics. 2021; 9 (9):996.
Chicago/Turabian StyleAndrea D’Ambrosio; Enrico Schiassi; Fabio Curti; Roberto Furfaro. 2021. "Pontryagin Neural Networks with Functional Interpolation for Optimal Intercept Problems." Mathematics 9, no. 9: 996.
In this paper, a geometrical investigation of the star sensor image is performed under dynamic conditions where the angular velocity effects are non-negligible. It is shown that, when the spacecraft is rotating, the streaks left by the stars’ signal onto the star sensor detector belong to portions of conic sections which features depend on the angles between the instantaneous rotation axis, the sensor line of sight and the stars’ direction. The geometrical properties discussed in the first part of the paper can be used to develop new numerical methods for the evaluation of the angular velocity. Hence, the chord method is proposed and discussed. This approach needs at least two stars in two successive images and, despite its simplicity, is quite effective to get a preliminary estimation of the spacecraft angular velocity in terms of direction and magnitude. Using the stars’ centroids from two successive images, the chord method evaluates the angular velocity direction as the intersection of the normals to the streaks. The proposed method is firstly presented by means of simple examples using some reference geometries, and then it is applied to real scenarios by using a high fidelity star sensor simulator. The pre-processing and processing of simulated images are discussed, presenting the geometrical techniques used to cluster the streaks and compute the centroids. Results are presented and discussed, validating the reported theoretical speculations.
Dario Spiller; Fabio Curti. A geometrical approach for the angular velocity determination using a star sensor. Acta Astronautica 2020, 1 .
AMA StyleDario Spiller, Fabio Curti. A geometrical approach for the angular velocity determination using a star sensor. Acta Astronautica. 2020; ():1.
Chicago/Turabian StyleDario Spiller; Fabio Curti. 2020. "A geometrical approach for the angular velocity determination using a star sensor." Acta Astronautica , no. : 1.
The paper focuses on the opportunity to use star sensors to help space situational awareness and space surveillance. Catalogs of orbiting satellites around Earth are usually established on ground-based measurements that rely on optical or radar data provided by instruments on Earth. However, space-based observations offer new opportunities, as they are unrelated to the weather and the circadian rhythm to which the ground system is subjected. Consequently, space-based optical observation systems can provide data without atmospheric distortion from different observer-to-target distances, enhancing the possibility to detect and catalog resident space objects, i.e. satellites and space debris. This work deals with the feasibility study of an innovative strategy, which consists in the use of a star sensor with a dedicated algorithm to run directly on-board. This approach minimizes the impact on the platform so that, from a theoretical point of view, every satellite with a star sensor can be used as a space surveillance observer. The output of the algorithm consists of a database of pre-processed objects, which are then post-processed on ground. Numerical tests on synthetic images provided by a high-fidelity simulator demonstrate the applicability of the proposed approach. The study has been conducted within the framework of the Italian Space Agency project SPOT - Star sensor image Processing for orbiting Objects deTection.
Dario Spiller; Edoardo Magionami; Vincenzo Schiattarella; Fabio Curti; Claudia Facchinetti; Luigi Ansalone; Alberto Tuozzi. On-orbit recognition of resident space objects by using star trackers. Acta Astronautica 2020, 177, 478 -496.
AMA StyleDario Spiller, Edoardo Magionami, Vincenzo Schiattarella, Fabio Curti, Claudia Facchinetti, Luigi Ansalone, Alberto Tuozzi. On-orbit recognition of resident space objects by using star trackers. Acta Astronautica. 2020; 177 ():478-496.
Chicago/Turabian StyleDario Spiller; Edoardo Magionami; Vincenzo Schiattarella; Fabio Curti; Claudia Facchinetti; Luigi Ansalone; Alberto Tuozzi. 2020. "On-orbit recognition of resident space objects by using star trackers." Acta Astronautica 177, no. : 478-496.
New results are presented for the problem of minimum-time control of a general linear time-invariant normal system evolving from an arbitrary initial state to an arbitrary final state (no-rest to no-rest problem), subjected to bound controls. In particular, it is demonstrated that the above problem is equivalent to an associated minimum-time control problem of transferring the same system from a particular initial state to the state-space origin (no-rest to rest problem), where that particular initial state is related to the boundary states of the original problem through a transformation of the state-space onto itself. If the optimal control history that transfers the system from an arbitrary initial state to the origin is known, either analytically or numerically, then the new results provide a method to solve the problem of minimum-time control between two arbitrary states and moreover, to find all of the extremal controlled trajectories. A criterion of existence is also given for the solution of the minimum-time control between two arbitrary states. Finally, the analytic solution is presented for the minimum-time control of the double integrator between arbitrary states. That solution provides a significant example of applying the new results.
Marcello Romano; Fabio Curti. Time-optimal control of linear time invariant systems between two arbitrary states. Automatica 2020, 120, 109151 .
AMA StyleMarcello Romano, Fabio Curti. Time-optimal control of linear time invariant systems between two arbitrary states. Automatica. 2020; 120 ():109151.
Chicago/Turabian StyleMarcello Romano; Fabio Curti. 2020. "Time-optimal control of linear time invariant systems between two arbitrary states." Automatica 120, no. : 109151.
A study on reconfiguration manoevres applied to a tetrahedral formation in highly elliptical orbits is proposed, by using a propellantless solution. The manoeuvring strategy consists in exploiting certain environmental forces, specifically those provided by solar radiation pressure and atmospheric drag, by actively controlling the satellites’ attitudes. Through inverse dynamics particle swarm optimization the optimal attitudes required for the manoeuvres are evaluated, whereas the configuration’s evolution is simulated by a high-fidelity orbital simulator. The goal of the reconfiguration problem is to find an optimal control in order for the four spacecraft to reach a desired configuration in a specified portion of orbit, where the desired configuration is evaluated by a shape and size geometric parameter. By increasing the manoeuvring time and the satellites’ area to mass ratio, all the case studies considered are successfully verified.
Rebecca La Norcia; Dario Spiller; Fabio Curti; Christian Circi. Formation flying reconfiguration manoeuvres via environmental forces in highly elliptical orbits. Advances in Space Research 2020, 67, 3409 -3425.
AMA StyleRebecca La Norcia, Dario Spiller, Fabio Curti, Christian Circi. Formation flying reconfiguration manoeuvres via environmental forces in highly elliptical orbits. Advances in Space Research. 2020; 67 (11):3409-3425.
Chicago/Turabian StyleRebecca La Norcia; Dario Spiller; Fabio Curti; Christian Circi. 2020. "Formation flying reconfiguration manoeuvres via environmental forces in highly elliptical orbits." Advances in Space Research 67, no. 11: 3409-3425.
This paper is devoted to the implementation and application of an improved version of the metaheuristic algorithm called magnetic charged system search. Some modifications and novelties are introduced and tested. Firstly, the authors’ attempt is to develop a self-adaptive and user-friendly algorithm which can automatically set all the preliminary parameters (such as the numbers of particles, the maximum iterations number) and the internal coefficients. Indeed, some mathematical laws are proposed to set the parameters and many coefficients can dynamically change during the optimization process based on the verification of internal conditions. Secondly, some strategies are suggested to enhance the performances of the proposed algorithm. A chaotic local search is introduced to improve the global best particle of each iteration by exploiting the features of ergodicity and randomness. Moreover, a novel technique is proposed to handle bad-defined boundaries; in fact, the possibility to self-enlarge the boundaries of the optimization variables is considered, allowing to achieve the global optimum even if it is located on the boundaries or outside. The algorithm is tested through some benchmark functions and engineering design problems, showing good results, followed by an application regarding the problem of time-suboptimal manoeuvres for satellite formation flying, where the inverse dynamics technique, together with the B-splines, is employed. This analysis proves the ability of the proposed algorithm to optimize control problems related to space engineering, obtaining better results with respect to more common and used algorithms in literature.
Andrea D’Ambrosio; Dario Spiller; Fabio Curti. Improved magnetic charged system search optimization algorithm with application to satellite formation flying. Engineering Applications of Artificial Intelligence 2020, 89, 103473 .
AMA StyleAndrea D’Ambrosio, Dario Spiller, Fabio Curti. Improved magnetic charged system search optimization algorithm with application to satellite formation flying. Engineering Applications of Artificial Intelligence. 2020; 89 ():103473.
Chicago/Turabian StyleAndrea D’Ambrosio; Dario Spiller; Fabio Curti. 2020. "Improved magnetic charged system search optimization algorithm with application to satellite formation flying." Engineering Applications of Artificial Intelligence 89, no. : 103473.
This paper addresses the problem of star identification in the presence of high slew rates, false objects and image deformations introduced by the rolling shutter. These problems can affect the operating life of star trackers and worsen the nominal performances. The proposed methodology relies on a technique named Improved Multi-Poles Algorithm, especially designed for robustness to false objects and slew rates. Angular velocities up to five degrees per second are considered so that stars are seen no more as near-circular spots but appear as streaks. The image deformation due to the rolling shutter of modern active pixel sensor detectors is compensated by means of a mathematical model based on a first order approximation of problem. A star tracker high fidelity simulator generates the input images considering typical noises due to the electronics and space environment. The reported results show that the proposed approach guarantees a reliable star identification and attitude determination with angular velocity from zero to five degrees per second.
Vincenzo Schiattarella; Dario Spiller; Fabio Curti. Star identification robust to angular rates and false objects with rolling shutter compensation. Acta Astronautica 2019, 166, 243 -259.
AMA StyleVincenzo Schiattarella, Dario Spiller, Fabio Curti. Star identification robust to angular rates and false objects with rolling shutter compensation. Acta Astronautica. 2019; 166 ():243-259.
Chicago/Turabian StyleVincenzo Schiattarella; Dario Spiller; Fabio Curti. 2019. "Star identification robust to angular rates and false objects with rolling shutter compensation." Acta Astronautica 166, no. : 243-259.
Dario Spiller; Robert G. Melton; Fabio Curti. Inverse dynamics particle swarm optimization applied to constrained minimum-time maneuvers using reaction wheels. Aerospace Science and Technology 2018, 75, 1 -12.
AMA StyleDario Spiller, Robert G. Melton, Fabio Curti. Inverse dynamics particle swarm optimization applied to constrained minimum-time maneuvers using reaction wheels. Aerospace Science and Technology. 2018; 75 ():1-12.
Chicago/Turabian StyleDario Spiller; Robert G. Melton; Fabio Curti. 2018. "Inverse dynamics particle swarm optimization applied to constrained minimum-time maneuvers using reaction wheels." Aerospace Science and Technology 75, no. : 1-12.
This paper deals with the problem of spacecraft time-optimal reorientation maneuvers under boundaries and path constraints. The minimum time solution with keep-out constraints is proposed using the particle swarm optimization technique. A novel method based on the evolution of the kinematics and the successive obtainment of the control law is presented and named as inverse dynamics particle swarm optimization. It is established that the computation of the minimum time maneuver with the proposed technique leads to near-optimal solutions, which fully satisfy all the boundaries and path constraints.
Dario Spiller; Luigi Ansalone; Fabio Curti. Particle Swarm Optimization for Time-Optimal Spacecraft Reorientation with Keep-Out Cones. Journal of Guidance, Control, and Dynamics 2016, 39, 312 -325.
AMA StyleDario Spiller, Luigi Ansalone, Fabio Curti. Particle Swarm Optimization for Time-Optimal Spacecraft Reorientation with Keep-Out Cones. Journal of Guidance, Control, and Dynamics. 2016; 39 (2):312-325.
Chicago/Turabian StyleDario Spiller; Luigi Ansalone; Fabio Curti. 2016. "Particle Swarm Optimization for Time-Optimal Spacecraft Reorientation with Keep-Out Cones." Journal of Guidance, Control, and Dynamics 39, no. 2: 312-325.
Optical observations constitute a source of angular measurements of a satellite pass. Commonly, these observations have short durations with respect to the satellite orbit period. As a consequence, the use of classical orbit determination algorithms, as Laplace, Gauss or Escobal methods, give very poor results. The present work faces with the problem of estimating the orbital parameters of an orbiting object using its optical streak acquired by a telescope or a high accuracy camera. In the paper a new technique is developed for the Initial Orbit Determination from optical data by exploiting the genetic algorithms. The algorithm works without restrictions on the observer location. A recent challenging problem is the Initial Orbit Determination with space-based observations. This work focuses on the problem of determinating the orbital parameters of a satellite from an orbiting observer in LEO, using short time observations. We present the results based on a simulation with the observer on a sun-synchronous orbit with a single observation of just 60 s. Monte Carlo simulations are presented with different levels of sensor accuracy to show the reliability of the algorithm. The algorithm is able to yield a candidate solution for each observation. The coplanar case is analyzed and discussed as well.
Luigi Ansalone; Fabio Curti. A genetic algorithm for Initial Orbit Determination from a too short arc optical observation. Advances in Space Research 2013, 52, 477 -489.
AMA StyleLuigi Ansalone, Fabio Curti. A genetic algorithm for Initial Orbit Determination from a too short arc optical observation. Advances in Space Research. 2013; 52 (3):477-489.
Chicago/Turabian StyleLuigi Ansalone; Fabio Curti. 2013. "A genetic algorithm for Initial Orbit Determination from a too short arc optical observation." Advances in Space Research 52, no. 3: 477-489.