Challenging science requirements and complex space missions are driving the need for fast and robust space trajectory design and simulation tools. The main aim of this thesis is to develop new and improved high performance algorithms and solution techniques for commonly encountered problems in astrodynamics. Five major problems are considered and their state-of-the art algorithms are systematically improved. Theoretical and methodological improvements are combined with modern computational techniques, resulting in increased algorithm robustness and faster runtime performance. The five selected problems are 1) Multiple revolution Lambert problem, 2) High-fidelity geopotential (gravity field) computation, 3) Ephemeris computation, 4) Fast and accurate sensitivity computation, and 5) High-fidelity multiple spacecraft simulation. The work being presented enjoys applications in a variety of fields like preliminary mission design, high-fidelity trajectory simulation, orbit estimation and numerical optimization. Other fields like space and environmental science to chemical and electrical engineering also stand to benefit.

Su abonentų pozicija geografinėje erdvėje susijusi informacija naudojama labai įvairiose srityse: greitajai pagalbai teikti (112 paslauga), teisėsaugoje, krovinių transportavime (stebima kur šiuo metu yra transportuojami kroviniai), turizme, eismo sąlygų stebėjimui, artimiausių ligoninių, restoranų, lankytinų vietų paieškai, pramogoms, mobiliojo tinklo struktūros planavimui (nustačius kur yra didesnis abonentų susibūrimas, pastatoma daugiau bazinių stočių). Tokia su objektų pozicijomis susijusi informacija kaupiama Judančių Objektų duomenų bazėse (JODB), kuri yra judančių objektų sekimo sistemos dalis. Judančiu objektu laikomas toks objektas, kuris bėgant laikui keičia savo geografinę ir laikinę poziciją trimatėje x,y,t erdvėje. Anksčiau vietos informacijai rinkti buvo naudojama tik GPS technologija. GPS technologijos pagrindinis trūkumas tas, kad ji sunkiai veikia miesto tipo vietovėse ir praktiškai neveikia požeminiuose ir antžeminiuose statiniuose. Tačiau vystantis įvairiomis mobiliosiomis ir bevielėms technologijoms, daugėjant jų naudojimo vietų, atsiranda galimybė tokius duomenis rinkti pasinaudojant ne tik GPS, bet ir GSM, WLAN, Bluetooth ir kitomis bevielėmis technologijomis. Todėl atsiranda galimybė GPS pagalba gautus vietos duomenis patikslinti, papildyti arba netgi, jei nereikalaujama didelio tikslumo, judančių objektų vietą nustatyti be GPS panaudojimo. Stebint judančius objektus „visur ir visada“ kiekvienam objektui susidaro baigtinis pozicijų skaičius per tam... [toliau žr. visą tekstą] / The usage of moving objects location information becomes very popular nowadays. This location information can be used in many places: for emergency purposes, tracking cars with cargos, animal tracking, tourism, etc. The moving object’s positions can be detected using location techniques, such as GPS, GSM, etc. When detected moving object’s position is kept in Moving Object Databases (MODB). When object’s position is detected constantly we get a lot of positions, which represent the movement of particular object. We can call this movement a trajectory. The main problem is that these trajectories are too big to keep them in database, to update them or to make a search among them. That’s why there is a need for effective trajectory compression methods in order to make trajectories smaller without losing the most important object’s movement information. Different location techniques generate different types of trajectories, so each type of trajectory needs a different approach how to apply compression technique to it. The trajectory compression can be applied while generating trajectory or it can be done when the generation of trajectory is finished. There are presented different trajectory compression methods for different location techniques (GPS, GSM) in this work. These methods are incorporated into location data history restoration system in order to apply them for location data compression. In this work statistical methods for evaluation of location data compression... [to full text]

Baigiamajame magistro darbe nagrinėjamas šešiakojo roboto judėjimas. Pateikiami vienos kojos atvirkštinės kinematikos uždavinio sprendimai Denavito ir Hartenbergo bei geometriniu metodais. Analizuojamas vienos kojos trajektorijos sudarymo metodas ir pateikiams jos aprašymo būdas. Pateikiami galimi trajektorijų pavyzdžiai. Sudaroma trikojės roboto eisenos seka bei diagrama. Darbe pateikiamas roboto valdymo algoritmas ir valdymo programa, atsižvelgiant į apibrėžtus variklių valdymo kriterijus. Eksperimentiškai tiriamas roboto judėjimas lygiu paviršiumi taikant trikoję eiseną. Pagal rezultatus koreguojama eisena. Atliekami trajektorijos pakartojimo tikslumo bandymai. Įvertinus rezultatus pateikiamos baigiamojo darbo išvados ir pasiūlymai. / Hexapod robot locomotion is analyzed in this paper. Inverse kinematics solutions are proposed for one leg using Denavit-Hartenberg and geometric methods. Trajectory forming for one leg is analyzed and solution for delineating trajectory is introduced. Possible leg trajectory examples are presented. Tripod gait sequence and diagram is designed for robot. Work presents robot control algorithm and program according to motor control parameters. Robot locomotion over regular terrain using tripod gait is tested. Gait then is corrected according to test results. Tests are made for trajectory repeating accuracy. Conclusions and solutions are made according to results.

In this thesis, the kinematic properties of Single Gimballed Control Moment Gyroscopes (SGCMGs) are investigated. Singularity phenomenon inherent to them is explained. Furthermore, existing steering laws with their derivations are given. A novel steering law is developed that may provide singularity avoidance or may be used for quick transition through a singularity with small torque errors. To avoid singularity angular momentum trajectory of the maneuver is to be simulated in advance for the calculation of singularity free gimbal histories. The steering law, besides accurately generating required torques, also pushes the system to follow trajectories closely if there is a small difference between the planned and the realized momentum histories. Thus, it may be used in a feedback system. Also presented are number of approaches for singularity avoidance or quick transition through a singularity. The application of these ideas to the feedback controlled spacecraft is also presented. Existing steering laws and the proposed method are compared through computer simulations. It is shown that the proposed steering law is very effective in singularity avoidance and quick transition through singularities. Furthermore, the approach is demonstrated to be repeatable even singularity is encountered.

This dissertation is focused on target trajectory identification using CW radar sensor network measuring. An omni-directional radar based on single mixing is considered for measurement in ballistic tunnel, where information about direction of target approaching is a priory known. Applied experimental radar network setup with system controller and acquisition units is demonstrated. Mathematical models and optimized structures have been developed for fitting of system parameters and presented in the theoretical part. The second part is aimed to the multi-trajectory identification. New methodical techniques of this work consist in identification of the points of the closest approach with V model function and utilizing gradient methods for path identification.

<p>The missed-thrust problem is a modern challenge in the field of mission design. While some methods exist to quantify its effects, there still exists room for improvement for algorithms which can fully anticipate and plan for a realistic set of missed-thrust events. The present work investigates the use of machine learning techniques to provide a robust controller for a low-thrust spacecraft. The spacecraft’s thrust vector is provided by a neural network controller which guides the spacecraft to the target along a trajectory that is robust to missed thrust, and the controller does not need to re-optimize any trajectories if it veers off its nominal course. The algorithms used to train the controller to account for missed thrust are supervised learning and neuroevolution. Supervised learning entails showing a neural network many examples of what inputs and outputs should look like, with the network learning over time to duplicate the patterns it has seen. Neuroevolution involves testing many neural networks on a problem, and using the principles of biological evolution and survival of the fittest to produce increasingly competitive networks. Preliminary results show that a controller designed with these methods provides mixed results, but performance can be greatly boosted if the controller’s output is used as an initial guess for an optimizer. With an optimizer, the success rate ranges from around 60% to 96% depending on the problem.</p> <p><br></p> <p>Additionally, this work conducts an analysis of a novel hyperbolic rendezvous strategy which was originally conceived by Dr. Buzz Aldrin. Instead of rendezvousing on the outbound leg of a hyperbolic orbit (traveling away from Earth), the spacecraft performs a rendezvous while on the inbound leg (traveling towards Earth). This allows for a relatively low Delta-v abort option for the spacecraft to return to Earth if a problem arose during rendezvous. Previous work that studied hyperbolic rendezvous has always assumed rendezvous on the outbound leg because the total Delta-v required (total propellant required) for the insertion alone is minimal with this strategy. However, I show that when an abort maneuver is taken into consideration, inserting on the inbound leg is both lower Delta-v overall, and also provides an abort window which is up to a full day longer.</p>

Comme les robots effectuent de plus en plus de tâches en interaction avec l'homme ou dans un environnement humain, ils doivent assurer la sécurité et le confort des hommes. Dans ce contexte, le robot doit adapter son comportement et agir en fonction des évolutions de l'environnement et des activités humaines. Les robots développés sur la base de l'apprentissage ou d'un planificateur de mouvement ne sont pas en mesure de réagir assez rapidement, c'est pourquoi nous proposons d'introduire un contrôleur de trajectoire intermédiaire dans l'architecture logicielle entre le contrôleur bas niveau et le planificateur de plus haut niveau. Le contrôleur de trajectoire que nous proposons est basé sur le concept de générateur de trajectoire en ligne (OTG), il permet de calculer des trajectoires en temps réel et facilite la communication entre les différents éléments, en particulier le planificateur de chemin, le générateur de trajectoire, le détecteur de collision et le contrôleur. Pour éviter de replanifier toute une trajectoire en réaction à un changement induit par un humain, notre contrôleur autorise la déformation locale de la trajectoire et la modification de la loi d'évolution pour accélérer ou décélérer le mouvement. Le contrôleur de trajectoire peut également commuter de la trajectoire initiale vers une nouvelle trajectoire. Les fonctions polynomiales cubiques que nous utilisons pour décrire les trajectoires fournissent des mouvements souples et de la flexibilité sans nécessiter de calculs complexes. De plus, les algorithmes de lissage que nous proposons permettent de produire des mouvements esthétiques ressemblants à ceux des humains. Ce travail, mené dans le cadre du projet ANR ICARO, a été intégré et validé avec les robots KUKA LWR de la plate-forme robotique du LAAS-CNRS. / In order to perform a large variety of tasks in interaction with human or in human environments, a robot needs to guarantee safety and comfort for humans. In this context, the robot shall adapt its behavior and react to the environment changes and human activities. The robots based on learning or motion planning are not able to adapt fast enough, so we propose to use a trajectory controller as an intermediate control layer in the software structure. This intermediate layer exchanges information with the low level controller and the high level planner. The proposed trajectory controller, based on the concept of Online Trajectory Generation (OTG), allows real time computation of trajectories and easy communication with the different components, including path planner, trajectory generator, collision checker and controller. To avoid the replan of an entire trajectory when reacting to a human behaviour change, the controller must allow deforming locally a trajectory or accelerate/decelerate by modifying the time function. The trajectory controller must also accept to switch from an initial trajectory to a new trajectory to follow. Cubic polynomial functions are used to describe trajectories, they provide smoothness, flexibility and computational simplicity. Moreover, to satisfy the objective of aesthetics, smoothing algorithm are proposed to produce human-like motions. This work, conducted as part of the ANR project ICARO, has been integrated and validated on the KUKA LWR robot platform of LAAS-CNRS.

This degree project addresses poaching challenges by employing predictive analysis of animal movements and their correlation with the dynamic environment using a machine learning approach. The goal is to provide accurate predictions of animal movements, enabling rangers to intercept potential threats and safeguard wildlife from snares. A wide analysis considers previous studies on animal movements and both animal and environment data availability. To efficiently represent the dynamic environment and correlate it with animal movement data, accurate matching of environment variables to each animal measurement is crucial. We selected multiple environment datasets to capture a sufficient amount ofenvironmental properties. Due to practical constraints, daily representation of the environment is not achievable, and weekly mean or monthly mode values are used instead. Data insights are obtained through the training of a regression neural network using the filtered environmental and animal movement data. The results highlight the significant role ofenvironmental features in predicting animal movements, emphasizing their importance for accurate predictions. Despite some offset and few erroneous predictions, a strong similarity between animal predicted trajectory and animal true trajectory was achieved, indicating that the model is capable to capture general patterns and to correctly tune in predictions of detailed movements as well. The overall offset of the trajectories is still a weak point of this model, but it may just indicate the presence of some underlying systematic error that can be corrected through further work. The integration of such a developed prediction model into existing frameworks could assist law enforcingauthorities in preventing poaching activities.

In this dissertation, we focus on the strategy that places and stabilizes the path of an aerial drogue, which is towed by a mothership aircraft using a long flexible cable, onto a horizontally flat orbit by maneuvering the mothership in the presence of wind. To achieve this goal, several studies for towed cable systems are conducted, which include the dynamic modeling for the cable, trajectory generation strategies for the mothership, trajectory-tracking control law design, and simulation and flight test implementations. First, a discretized approximation method based on finite element and lumped mass is employed to establish the mathematical model for the towed cable system in the simulation. Two approaches, Gauss's Principle and Newton's second law, are utilized to derive the equations of motion for inelastic and elastic cables, respectively. The preliminary studies for several key parameters of the system are conducted to learn their sensitivities to the system motion in the steady state. Flight test results are used to validate the mathematical model as well as to determine an appropriate number of cable links. Furthermore, differential flatness and model predictive control based methods are used to produce a mothership trajectory that leads the drogue onto a desired orbit. Different desired drogue orbits are utilized to generate required mothership trajectories in different wind conditions. The trajectory generation for a transitional flight in which the system flies from a straight and level flight into a circular orbit is also presented. The numerical results are presented to illustrate the required mothership orbits and its maneuverability in different wind conditions. A waypoint following based strategy for mothership to track its desired trajectory in flight test is developed. The flight test results are also presented to illustrate the effectiveness of the trajectory generation methods. In addition, a nonlinear time-varying feedback control law is developed to regulate the mothership to follow the desired trajectory in the presence of wind. Cable tensions and wind disturbance are taken into account in the design model and Lyapunov based backstepping technique is employed to develop the controller. The mothership tracking error is proved to be capable of exponentially converging to an ultimate bound, which is a function of the upper limit of the unknown component of the wind. The simulation results are presented to validate the controller. Finally, a trajectory-tracking strategy for unmanned aerial vehicles is developed where the autopilot is involved in the feedback controller design. The trajectory-tracking controller is derived based on a generalized design model using Lyapunov based backstepping. The augmentations of the design model and trajectory-tracking controller are conducted to involve the autopilot in the closed-loop system. Lyapunov stability theory is used to guarantee the augmented controller is capable of driving the vehicle to exponentially converge to and follow the desired trajectory with the other states remaining bounded. Numerical and Software-In-the-Loop simulation results are presented to validate the augmented controller. This method presents a framework of implementing the developed trajectory-tracking controllers for unmanned aerial vehicles without any modification to the autopilot.

A large proportion of movement in urban area is constrained to a road network such as pedestrian, bicycle and vehicle. That movement information is commonly collected by Global Positioning System (GPS) sensor, which has generated large collections of trajectories. A contiguous sequential pattern (CSP) in these trajectories represents a certain number of objects traversing a sequence of spatially contiguous edges in the network, which is an intuitive way to study regularities in network-constrained movement. CSPs are closely related to route choices and traffic flows and can be useful in travel demand modeling and transportation planning. However, the efficient and scalable extraction of CSPs and effective visualization of the heavily overlapping CSPs are remaining challenges. To address these challenges, the thesis develops two algorithms and a visual analytics system. Firstly, a fast map matching (FMM) algorithm is designed for matching a noisy trajectory to a sequence of edges traversed by the object with a high performance. Secondly, an algorithm called bidirectional pruning based closed contiguous sequential pattern mining (BP-CCSM) is developed to extract sequential patterns with closeness and contiguity constraint from the map matched trajectories. Finally, a visual analytics system called sequential pattern explorer for trajectories (SPET) is designed for interactive mining and visualization of CSPs in a large collection of trajectories. Extensive experiments are performed on a real-world taxi trip GPS dataset to evaluate the algorithms and visual analytics system. The results demonstrate that FMM achieves a superior performance by replacing repeated routing queries with hash table lookups. BP-CCSM considerably outperforms three state-of-the-art algorithms in terms of running time and memory consumption. SPET enables the user to efficiently and conveniently explore spatial and temporal variations of CSPs in network-constrained movement. / <p>QC 20171122</p>