Analysis and Comparison of Clothoid and Dubins Algorithms for UAV Trajectory Generation

The differences between two types of pose-based UAV path generation methods clothoid and Dubins are analyzed in this thesis. The Dubins path is a combination of circular arcs and straight line segments; therefore its curvature will exhibit sudden jumps between constant values. The resulting path will have a minimum length if turns are performed at the minimum possible turn radius. The clothoid path consists of a similar combination of arcs and segments but the difference is that the clothoid arcs have a linearly variable curvature and are generated based on Fresnel integrals. Geometrically, the generation of the clothoid arc starts with a large curvature that decreases to zero. The clothoid path results are longer than the Dubins path between the same two poses and for the same minimum turn radius. These two algorithms are the focus of this research because of their geometrical simplicity, flexibility, and low computational requirements.;The comparison between clothoid and Dubins algorithms relies on extensive simulation results collected using an ad-hoc developed automated data acquisition tool within the WVU UAV simulation environment. The model of a small jet engine UAV has been used for this purpose. The experimental design considers several primary factors, such as different trajectory tracking control laws, normal and abnormal flight conditions, relative configuration of poses, and wind and turbulence. A total of five different controllers have been considered, three conventional with fixed parameters and two adaptive. The abnormal flight conditions include locked or damaged actuators (stabilator, aileron, or rudder) and sensor bias affecting roll, pitch, or yaw rate gyros that are used in the feedback control loop. The relative configuration of consecutive poses is considered in terms of heading (required turn angle) and relative location of start and end points (position quadrant). Wind and turbulence effects were analyzed for different wind speed and direction and several levels of turbulence severity. The evaluation and comparison of the two path generation algorithms are performed based on generated and actual path length and tracking performance assessed in terms of tracking errors and control activity.;Although continuous position and velocity are ensured, the Dubins path yields discontinuous changes in path curvature and hence in commanded lateral accelerations at the transition points between the circular arcs and straight segments. The simulation results show that this generally leads to increased trajectory tracking errors, longer actual paths, and more intense control surface activity. The gradual (linear) change in clothoid curvature yields a continuous change in commanded lateral accelerations with general positive effects on the overall UAV performance based on the metrics considered. The simulation results show general similar trends for all factors considered. As a result, it may be concluded that, due to the continuous change in commanded lateral acceleration, the clothoid path generation algorithm provides overall better performance than the Dubins algorithm, at both normal and abnormal flight conditions, if the UAV mission involves significant maneuvers requiring intense lateral acceleration commands

Development of an Integrated Intelligent Multi -Objective Framework for UAV Trajectory Generation

This thesis explores a variety of path planning and trajectory generation schemes intended for small, fixed-wing Unmanned Aerial Vehicles. Throughout this analysis, discrete and pose-based methods are investigated. Pose-based methods are the focus of this research due to their increased flexibility and typically lower computational overhead.;Path planning in 3 dimensions is also performed. The 3D Dubins methodology presented is an extension of a previously suggested approach and addresses both the mathematical formulation of the methodology, as well as an assessment of numerical issues encountered and the solutions implemented for these.;The main contribution of this thesis is a 3-dimensional clothoid trajectory generation algorithm, which produces flyable paths of continuous curvature to ensure a more followable commanded path. This methodology is an extension of the 3D Dubins method and the 2D clothoid method, which have been implemented herein. To ensure flyability of trajectories produced by 3D pose-based trajectory generation methodologies, a set of criteria are specified to limit the possible solutions to only those flyable by the aircraft. Additionally, several assumptions are made concerning the motion of the aircraft in order to simplify the path generation problem.;The 2D and 3D clothoid and Dubins trajectory planners are demonstrated through a trajectory tracking performance comparison between first the 2D Dubins and 2D clothoid methods using a position proportional-integral-derivative controller, then the 3D Dubins and 3D clothoid methods using both a position proportional-integral-derivative controller and an outer-loop non-linear dynamic inversion controller, within the WVU UAV Simulation Environment. These comparisons are demonstrated for both nominal and off-nominal conditions, and show that for both 2D and 3D implementations, the clothoid path planners yields paths with better trajectory tracking performance as compared to the Dubins path planners.;Finally, to increase the effectiveness and autonomy of these pose-based trajectory generation methodologies, an immunity-based evolutionary optimization algorithm is developed to select a viable and locally-optimal trajectory through an environment while observing desired points of interest and minimizing threat exposure, path length, and estimated fuel consumption. The algorithm is effective for both 2D and 3D routes, as well as combinations thereof. A brief demonstration is provided for this algorithm. Due to the calculation time requirements, this algorithm is recommended for offline use

A Flexible Modeling Approach for Robust Multi-Lane Road Estimation

A robust estimation of road course and traffic lanes is an essential part of environment perception for next generations of Advanced Driver Assistance Systems and development of self-driving vehicles. In this paper, a flexible method for modeling multiple lanes in a vehicle in real time is presented. Information about traffic lanes, derived by cameras and other environmental sensors, that is represented as features, serves as input for an iterative expectation-maximization method to estimate a lane model. The generic and modular concept of the approach allows to freely choose the mathematical functions for the geometrical description of lanes. In addition to the current measurement data, the previously estimated result as well as additional constraints to reflect parallelism and continuity of traffic lanes, are considered in the optimization process. As evaluation of the lane estimation method, its performance is showcased using cubic splines for the geometric representation of lanes in simulated scenarios and measurements recorded using a development vehicle. In a comparison to ground truth data, robustness and precision of the lanes estimated up to a distance of 120 m are demonstrated. As a part of the environmental modeling, the presented method can be utilized for longitudinal and lateral control of autonomous vehicles

Path Planning for Aircraft Under Threat of Detection from Ground-Based Radar with Uncertainty in Aircraft and Radar States

Mission planners for manned and unmanned aircraft operating within the detection range of ground-based radar systems are often concerned with the probability of detection. Several factors influence the probability of detection, including aircraft position and orientation, radar position, and radar performance parameters. Current path planning algorithms assume that these factors are known with certainty, but in practice, these factors are estimated and have some uncertainty. This dissertation explores methods to consider the uncertainty in the detection factors for an aircraft path planner. First, the detection model is extended to include uncertainty in the aircraft position and orientation, radar position, and radar parameters. Second, an efficient method to estimate the aircraft position and orientation uncertainty is presented that enables rapid path evaluation. Third, the extended radar model and efficient aircraft uncertainty calculation are incorporated into a path planner that evaluates the sources of uncertainty and provides actionable information to the mission planner

Smooth Three-Dimensional Route Planning for Fixed-Wing Unmanned Aerial Vehicles With Double Continuous Curvature

This paper presents a smooth flight path planner for maneuvering in a 3D Euclidean space, which is based on two new space curves. The first one is called 'Elementary Clothoid-based 3D Curve (ECb3D)', which is built by concatenating two symmetric Clothoid-based 3D Curves (Cb3D). The combination of these curves allows to reach an arbitrary orientation in 3D Euclidean space. This new curve allows to generate continuous curvature and torsion profiles that start and finish with a null value, which means that they can be concatenated with other curves, such as straight segments, without generating discontinuities on those variables. The second curve is called 'Double Continuous Curvature 3D Curve (DCC3D)' which is built as a concatenation of three straight line segments and two ECb3D curves, allowing to reach an arbitrary configuration in position and orientation in the 3D Euclidean space without discontinuities in curvature and torsion. This trajectory is applied for autonomous path planning and navigation of unmanned aerial vehicles (UAVs) such as fixed-wing aircrafts. Finally, the results are validated on the FlightGear 2018 flight simulator with the UAV kadett 2400 platform

Formation Control Using Vehicle Operational Envelopes and Behavior-Based Dual-Mode Model Predictive Control

This thesis presents a control framework for formation control. Given an initial desired trajectory, a framework is presented to generate trajectories for each vehicle within the formation. When combined with an operational envelope, a designated area for each vehicle to maneuver, for each vehicle the multi-vehicle formation control problem can be redefined into a single vehicle problem. A single vehicle framework is presented to track the respective trajectory when possible, or stay near it when it passes through previously unknown obstacles. Arc-based motions are used to rapidly produce desirable robot controls while a trajectory tracking motion is used to ensure that the vehicle tracks the trajectory when it is obstacle free. The resulting formation control framework is illustrated through a real-time simulation with trajectories passing through obstacles. The simulated robot is able to seamlessly balance tracking with obstacle avoidance

Path following hybrid control for vehicle stability applied to industrial forklifts

The paper focuses on a closed-loop hybrid controller (kinematic and dynamic) for path following approaches with industrial forklifts carrying heavy loads at high speeds, where aspects such as vehicle stability, safety, slippage and comfort are considered. The paper first describes a method for generating Double Continuous Curvature (DCC) paths for non-holonomic wheeled mobile robots, which is the basis of the proposed kinematic controller. The kinematic controller generates a speed profile, based on slow-in and fast-out policy, and a curvature profile recomputing DCC paths in closed-loop. The dynamic controller determines maximum values for decelerations and curvatures, as well as bounded sharpness so that instantaneous vehicle stability conditions can be guaranteed against lateral and frontal tip-overs. One of the advantages of the proposed method, with respect to full dynamic controllers, is that it does not require dynamic parameters to be estimated for modelling, which in general can be a difficult task. The proposed kinematic dynamic controller is afterwards compared with a classic kinematic controller like Pure-Pursuit. For that purpose, in our hybrid control structure we have just replaced the proposed kinematic controller with Pure-Pursuit. Several metrics, such as settling time, overshoot, safety and comfort have been analysed.This work was supported by VALi+d and PROMETEO Programs (Conselleria d'Educacio, Generalitat Valenciana), DIVISAMOS (DPI-2009-14744-C03-01) and SAFEBUS (IPT-2011-1165-370000): Ministry of Economy and Competitivity.Girbés, V.; Armesto Ángel, L.; Tornero Montserrat, J. (2014). Path following hybrid control for vehicle stability applied to industrial forklifts. Robotics and Autonomous Systems. 62(6):910-922. https://doi.org/10.1016/j.robot.2014.01.004S91092262

Clothoid-based Planning and Control in Intelligent Vehicles (Autonomous and Manual-Assisted Driving)

[EN] Nowadays, there are many electronic products that incorporate elements and features coming from the research in the field of mobile robotics. For instance, the well-known vacuum cleaning robot Roomba by iRobot, which belongs to the field of service robotics, one of the most active within the sector. There are also numerous autonomous robotic systems in industrial warehouses and plants. It is the case of Autonomous Guided Vehicles (AGVs), which are able to drive completely autonomously in very structured environments. Apart from industry and consumer electronics, within the automotive field there are some devices that give intelligence to the vehicle, derived in most cases from advances in mobile robotics. In fact, more and more often vehicles incorporate Advanced Driver Assistance Systems (ADAS), such as navigation control with automatic speed regulation, lane change and overtaking assistant, automatic parking or collision warning, among other features. However, despite all the advances there are some problems that remain unresolved and can be improved. Collisions and rollovers stand out among the most common accidents of vehicles with manual or autonomous driving. In fact, it is almost impossible to guarantee driving without accidents in unstructured environments where vehicles share the space with other moving agents, such as other vehicles and pedestrians. That is why searching for techniques to improve safety in intelligent vehicles, either autonomous or manual-assisted driving, is still a trending topic within the robotics community. This thesis focuses on the design of tools and techniques for planning and control of intelligent vehicles in order to improve safety and comfort. The dissertation is divided into two parts, the first one on autonomous driving and the second one on manual-assisted driving. The main link between them is the use of clothoids as mathematical formulation for both trajectory generation and collision detection. Among the problems solved the following stand out: obstacle avoidance, rollover avoidance and advanced driver assistance to avoid collisions with pedestrians.[ES] En la actualidad se comercializan infinidad de productos de electrónica de consumo que incorporan elementos y características procedentes de avances en el sector de la robótica móvil. Por ejemplo, el conocido robot aspirador Roomba de la empresa iRobot, el cual pertenece al campo de la robótica de servicio, uno de los más activos en el sector. También hay numerosos sistemas robóticos autónomos en almacenes y plantas industriales. Es el caso de los vehículos autoguiados (AGVs), capaces de conducir de forma totalmente autónoma en entornos muy estructurados. Además de en la industria y en electrónica de consumo, dentro del campo de la automoción también existen dispositivos que dotan de cierta inteligencia al vehículo, derivados la mayoría de las veces de avances en robótica móvil. De hecho, cada vez con mayor frecuencia los vehículos incorporan sistemas avanzados de asistencia al conductor (ADAS por sus siglas en inglés), tales como control de navegación con regulación automática de velocidad, asistente de cambio de carril y adelantamiento, aparcamiento automático o aviso de colisión, entre otras prestaciones. No obstante, pese a todos los avances siguen existiendo problemas sin resolver y que pueden mejorarse. La colisión y el vuelco destacan entre los accidentes más comunes en vehículos con conducción tanto manual como autónoma. De hecho, la dificultad de conducir en entornos desestructurados compartiendo el espacio con otros agentes móviles, tales como coches o personas, hace casi imposible garantizar la conducción sin accidentes. Es por ello que la búsqueda de técnicas para mejorar la seguridad en vehículos inteligentes, ya sean de conducción autónoma o manual asistida, es un tema que siempre está en auge en la comunidad robótica. La presente tesis se centra en el diseño de herramientas y técnicas de planificación y control de vehículos inteligentes, para la mejora de la seguridad y el confort. La disertación se ha dividido en dos partes, la primera sobre conducción autónoma y la segunda sobre conducción manual asistida. El principal nexo de unión es el uso de clotoides como elemento de generación de trayectorias y detección de colisiones. Entre los problemas que se resuelven destacan la evitación de obstáculos, la evitación de vuelcos y la asistencia avanzada al conductor para evitar colisiones con peatones.[CA] En l'actualitat es comercialitzen infinitat de productes d'electrònica de consum que incorporen elements i característiques procedents d'avanços en el sector de la robòtica mòbil. Per exemple, el conegut robot aspirador Roomba de l'empresa iRobot, el qual pertany al camp de la robòtica de servici, un dels més actius en el sector. També hi ha nombrosos sistemes robòtics autònoms en magatzems i plantes industrials. És el cas dels vehicles autoguiats (AGVs), els quals són capaços de conduir de forma totalment autònoma en entorns molt estructurats. A més de en la indústria i en l'electrònica de consum, dins el camp de l'automoció també existeixen dispositius que doten al vehicle de certa intel·ligència, la majoria de les vegades derivats d'avanços en robòtica mòbil. De fet, cada vegada amb més freqüència els vehicles incorporen sistemes avançats d'assistència al conductor (ADAS per les sigles en anglés), com ara control de navegació amb regulació automàtica de velocitat, assistent de canvi de carril i avançament, aparcament automàtic o avís de col·lisió, entre altres prestacions. No obstant això, malgrat tots els avanços segueixen existint problemes sense resoldre i que poden millorar-se. La col·lisió i la bolcada destaquen entre els accidents més comuns en vehicles amb conducció tant manual com autònoma. De fet, la dificultat de conduir en entorns desestructurats compartint l'espai amb altres agents mòbils, tals com cotxes o persones, fa quasi impossible garantitzar la conducció sense accidents. És per això que la recerca de tècniques per millorar la seguretat en vehicles intel·ligents, ja siguen de conducció autònoma o manual assistida, és un tema que sempre està en auge a la comunitat robòtica. La present tesi es centra en el disseny d'eines i tècniques de planificació i control de vehicles intel·ligents, per a la millora de la seguretat i el confort. La dissertació s'ha dividit en dues parts, la primera sobre conducció autònoma i la segona sobre conducció manual assistida. El principal nexe d'unió és l'ús de clotoides com a element de generació de trajectòries i detecció de col·lisions. Entre els problemes que es resolen destaquen l'evitació d'obstacles, l'evitació de bolcades i l'assistència avançada al conductor per evitar col·lisions amb vianants.Girbés Juan, V. (2016). Clothoid-based Planning and Control in Intelligent Vehicles (Autonomous and Manual-Assisted Driving) [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/65072TESI

Immunity-Based Framework for Autonomous Flight in GPS-Challenged Environment

In this research, the artificial immune system (AIS) paradigm is used for the development of a conceptual framework for autonomous flight when vehicle position and velocity are not available from direct sources such as the global navigation satellite systems or external landmarks and systems. The AIS is expected to provide corrections of velocity and position estimations that are only based on the outputs of onboard inertial measurement units (IMU). The AIS comprises sets of artificial memory cells that simulate the function of memory T- and B-cells in the biological immune system of vertebrates. The innate immune system uses information about invading antigens and needed antibodies. This information is encoded and sorted by T- and B-cells. The immune system has an adaptive component that can accelerate and intensify the immune response upon subsequent infection with the same antigen. The artificial memory cells attempt to mimic these characteristics for estimation error compensation and are constructed under normal conditions when all sensor systems function accurately, including those providing vehicle position and velocity information. The artificial memory cells consist of two main components: a collection of instantaneous measurements of relevant vehicle features representing the antigen and a set of instantaneous estimation errors or correction features, representing the antibodies. The antigen characterizes the dynamics of the system and is assumed to be correlated with the required corrections of position and velocity estimation or antibodies. When the navigation source is unavailable, the currently measured vehicle features from the onboard sensors are matched against the AIS antigens and the corresponding corrections are extracted and used to adjust the position and velocity estimation algorithm and provide the corrected estimation as actual measurement feedback to the vehicle’s control system. The proposed framework is implemented and tested through simulation in two versions: with corrections applied to the output or the input of the estimation scheme. For both approaches, the vehicle feature or antigen sets include increments of body axes components of acceleration and angular rate. The correction feature or antibody sets include vehicle position and velocity and vehicle acceleration adjustments, respectively. The impact on the performance of the proposed methodology produced by essential elements such as path generation method, matching algorithm, feature set, and the IMU grade was investigated. The findings demonstrated that in all cases, the proposed methodology could significantly reduce the accumulation of dead reckoning errors and can become a viable solution in situations where direct accurate measurements and other sources of information are not available. The functionality of the proposed methodology and its promising outcomes were successfully illustrated using the West Virginia University unmanned aerial system simulation environment