77 research outputs found
Safe Low-Altitude Navigation in Steep Terrain with Fixed-Wing Aerial Vehicles
Fixed-wing aerial vehicles provide an efficient way to navigate long
distances or cover large areas for environmental monitoring applications. By
design, they also require large open spaces due to limited maneuverability.
However, strict regulatory and safety altitude limits constrain the available
space. Especially in complex, confined, or steep terrain, ensuring the vehicle
does not enter an inevitable collision state(ICS) can be challenging. In this
work, we propose a strategy to find safe paths that do not enter an ICS while
navigating within tight altitude constraints. The method uses periodic paths to
efficiently classify ICSs. A sampling-based planner creates collision-free and
kinematically feasible paths that begin and end in safe periodic (circular)
paths. We show that, in realistic terrain, using circular periodic paths can
simplify the goal selection process by making it yaw agnostic and constraining
yaw. We demonstrate our approach by dynamically planning safe paths in
real-time while navigating steep terrain on a flight test in complex alpine
terrain.Comment: Accepted to IEEE Robotics and Automation Letters (RA-L
Development of Return to Base Flight Trajectory Generator Based on Dubins Path - Vector Field Method
In a Return to Base (RTB) situation, aircraft needs to immediately fly back to its origin airport. Since there is no published flight procedure for an RTB, an Air Traffic Controller (ATC) will assist the pilot for the flight procedure to fly. The objective of this work is to generate a flight trajectory in RTB situation based on the available airport flight procedures (departure and arrival) in Kertajati airport. The Dubins Path was used as a method to generate the flight trajectory and supported by the Vector-Field Methodology. The Python programming simulation was used to simulate the flight trajectory generation in the normal condition, second closest waypoint condition, and different parameters value condition. The trajectory was simulated based on flight characteristic of a single engine aircraft (Cesna 172) and multi-engine aircrafts (Boeing 737-800NG). The simulation results show that the Dubins Path and Vector-Field methodology success to generate the flight trajectory in different types of condition and parameters. The increase in aircraft velocity and the decrease in aircraft bank angle caused an increase in the aircraft turning radius. While, the decrease in aircraft flight path angle caused increase in the length of Dubins Path line
ON-BOARD ARTIFICIAL INTELLIGENCE FOR FAILURE DETECTION AND SAFE TRAJECTORY GENERATION
The use of autonomous flight vehicles has recently increased due to their versatility and capability of carrying out different type of missions in a wide range of flight conditions. Adequate commanded trajectory generation and modification, as well as high-performance trajectory tracking control laws have been an essential focus of researchers given that integration into the National Air Space (NAS) is becoming a primary need. However, the operational safety of these systems can be easily affected if abnormal flight conditions are present, thereby compromising the nominal bounds of design of the system\u27s flight envelop and trajectory following. This thesis focuses on investigating methodologies for modeling, prediction, and protection of autonomous vehicle trajectories under normal and abnormal flight conditions. An Artificial Immune System (AIS) framework is implemented for fault detection and identification in combination with the multi-goal Rapidly-Exploring Random Tree (RRT*) path planning algorithm to generate safe trajectories based on a reduced flight envelope. A high-fidelity model of a fixed-wing unmanned aerial vehicle is used to demonstrate the capabilities of the approach by timely generating safe trajectories as an alternative to original paths, while integrating 3D occupancy maps to simulate obstacle avoidance within an urban environment
Planning Visual Inspection Tours for a 3D Dubins Airplane Model in an Urban Environment
This paper investigates the problem of planning a minimum-length tour for a
three-dimensional Dubins airplane model to visually inspect a series of targets
located on the ground or exterior surface of objects in an urban environment.
Objects are 2.5D extruded polygons representing buildings or other structures.
A visibility volume defines the set of admissible (occlusion-free) viewing
locations for each target that satisfy feasible airspace and imaging
constraints. The Dubins traveling salesperson problem with neighborhoods
(DTSPN) is extended to three dimensions with visibility volumes that are
approximated by triangular meshes. Four sampling algorithms are proposed for
sampling vehicle configurations within each visibility volume to define
vertices of the underlying DTSPN. Additionally, a heuristic approach is
proposed to improve computation time by approximating edge costs of the 3D
Dubins airplane with a lower bound that is used to solve for a sequence of
viewing locations. The viewing locations are then assigned pitch and heading
angles based on their relative geometry. The proposed sampling methods and
heuristics are compared through a Monte-Carlo experiment that simulates view
planning tours over a realistic urban environment.Comment: 18 pages, 10 figures, Presented at 2023 SciTech Intelligent Systems
in Guidance Navigation and Control conferenc
Unmanned Aerial Vehicle (UAV) mission planning based on Fast Marching Square (FM²) planner and Differential Evolution (DE)
Nowadays, mission planning for Unmanned Aerial Vehicles (UAVs) is a very attractive
research field. UAVs have been a research focus for many purposes. In military
and civil fields, the UAVs are very used for different missions. Many of these studies
require a path planning to perform autonomous flights. Several problems related to
the physical limitations of the UAV arise when the planning is carried out, as well as
the maintenance of a fixed flight level with respect to the ground to capture videos
or overlying images.
This work presents an approach to plan missions for UAVs keeping a fixed flight
level constraint. An approach is proposed to solve these problems and to generate
effective paths in terms of smoothness and safety distance in two different types of
environments: 1) 3D urban environments and 2) open field with non-uniform terrain
environments.
Many proposed activities to be carried out by UAVs in whatever the environment
require a control over the altitude for different purposes: energy saving and
minimization of costs are some of these objectives. In general terms, the planning
is required to avoid all obstacles encountered in the environment and to maintain
a fixed flight level during the path execution. For this reason, a mission planning
requires robust planning methods.
The method used in this work as planner is the Fast Marching Square (FM2)
method, which generates a path free of obstacles. As a novelty, the method proposed
includes two adjustment parameters. Depending on the values of these parameters,
the restriction of flight level can be modified, as well as the smoothness and safety
margins from the obstacles of the generated paths. The Dubins airplane model
is used to check if the path resulting from the FM2 is feasible according to the
constraints of the UAV: its turning rate, climb rate and cruise speed.
Besides, this research also presents a novel approach for missions of Coverage
Path Planning (CPP) carried out by UAVs in 3D environments. These missions are
focused on path planning to cover a certain area in an environment in order to carry
out tracking, search or rescue tasks. The methodology followed uses an optimization
process based on the Differential Evolution (DE) algorithm in combination with the
FM2 planner.
Finally, the UAVs formation problem is introduced and addressed in a first stage
using the planner proposed in this thesis.
A wide variety of simulated experiments have been carried out to illustrate the
efficiency and robustness of the approaches presented, obtaining successful results
in different urban and open field 3D environments.Hoy en día la planificación de misiones para vehículos aéreos no tripulados (UAV)
es un campo de investigación muy atractivo. Los UAV son foco de investigación
en numerosas aplicaciones, tanto en el campo civil como militar. Muchas de estas
aplicaciones requieren de un sistema de planificación de ruta que permita realizar
vuelos autónomos y afrontar problemas relacionados con las limitaciones físicas del
UAV y con requerimientos como el nivel de vuelo sobre el suelo para, entre otras
funciones, poder capturar videos o imágenes.
Este trabajo presenta una propuesta de planificador para vehículos aéreos no
tripulados que permite resolver los problemas citados previamente, incluyendo en la
planificación las consideraciones cinemáticas del UAV y las restricciones de nivel de
vuelo, generando rutas suaves, realizables y suficientemente seguras para dos tipos
diferentes de entornos 3D: 1) entornos urbanos y 2) campos abiertos con terrenos
no uniformes.
El método utilizado en esta tesis como base para la planificación es el método
Fast Marching Square (FM2), que genera un camino libre de obstáculos. Como
novedad, el método propuesto incluye dos parámetros de ajuste. Dependiendo de
los valores de estos parámetros, se puede modificar la restricción de nivel de vuelo,
así como la suavidad y los márgenes de seguridad respecto a los obstáculos de las
rutas generadas. El modelo cinemático de Dubins se utiliza para verificar si la ruta
resultante de nuestro planificador es realizable de acuerdo con las restricciones del
UAV: su velocidad de giro, velocidad de ascenso y velocidad de crucero.
Además, esta tesis también presenta una propuesta novedosa para la planificación
de misiones de Coverage Path Planning (CPP) en entornos 3D. Estas misiones se
centran en la planificación de rutas para cubrir un área determinada de un entorno
con el fin de llevar a cabo tareas de rastreo, búsqueda o rescate. La metodología
seguida utiliza un proceso de optimización basado en el algoritmo Differential Evolution
(DE) en combinación con nuestro planificador FM2.
Como parte final de la tesis, el problema de formación de UAVs se introduce y
aborda en una primera etapa utilizando el planificador FM2 propuesto.Programa Oficial de Doctorado en Ingeniería Eléctrica, Electrónica y AutomáticaPresidente: Antonio Giménez Fernández.- Secretario: Luis Santiago Garrido Bullón.- Vocal: Raúl Suárez Feijó
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