260 research outputs found
Optimal Trajectory Tracking for an Autonomous UAV
The aim of the present project is the design of optimal flight trajectories for an automomous aerial vehicle which is expected to reach the desired locations in the operational environment expressed in terms of planned waypoints. The navigation must be performed with the vehicle's best effort, i.e. with the lowest cost. Hence, we want to minimize the input energy, a function of the inputs for the mathematical model which describes the dynamics of the vehicle. The trajectory must satisfy all the constraints and pass through all the planned waypoints. Assuming the vehicle as a point mass model, the best solution has been investigated through a genetic algorithm search procedure. The optimisation problem has been solved by modifying a micro-genetic algorithm software which was initially developed by D.L. Carroll. Between all the possible trajectories we select the more "realistic" connections among the waypoints. First of all, we have left out the trajectories with discontinuity in the derivatives as these are not feasible by the real aircraft. The polynomial spline is a suitable candidate to solve our problem. The algorithm splits the trajectory in sub-trajectories which join a sequence of three waypoints. Starting from the first three waypoints, the following sub-trajectories are superimposed keeping the first waypoint coincident with the last of the previous sub-trajectory. The sequence of polynomials is initialized assuming that jumps in the direction of flight are avoided pointing the heading angle in the presumed direction of flight. The optimal trajectory is a trade-off amongst three factors: the required energy cost, the minimum distance from the required waypoint and the feasibility of the trajectory. Results obtained with this optimization procedure are presente
Flat trajectory design and tracking with saturation guarantees: a nano-drone application
International audienceThis paper deals with the problem of trajectory planning and tracking of a quadcopter system based on the property of differential flatness. First, B-spline characterisations of the flat output allow for optimal trajectory generation subject to waypoint constraints, thrust and angle constraints while minimising the trajectory length. Second, the proposed tracking control strategy combines feedback linearisation and nested saturation control via flatness. The control strategy provides bounded inputs (thrust, roll and pitch angles) while ensuring the overall stability of the tracking error dynamics. The control parameters are chosen based on the information of the a priori given reference trajectory. Moreover, conditions for the existence of these parameters are presented. The effectiveness of the trajectory planning and the tracking control design is analysed and validated through simulation and experimental results over a real nano-quadcopter platform, the Crazyflie 2.0
Path Planning For Persistent Surveillance Applications Using Fixed-Wing Unmanned Aerial Vehicles
This thesis addresses coordinated path planning for fixed-wing Unmanned Aerial Vehicles
(UAVs) engaged in persistent surveillance missions. While uniquely suited to this mission,
fixed wing vehicles have maneuver constraints that can limit their performance in this role.
Current technology vehicles are capable of long duration flight with a minimal acoustic
footprint while carrying an array of cameras and sensors. Both military tactical and civilian
safety applications can benefit from this technology. We make three main contributions:
C1 A sequential path planner that generates a C2 flight plan to persistently acquire a
covering set of data over a user designated area of interest. The planner features the
following innovations:
• A path length abstraction that embeds kino-dynamic motion constraints to estimate feasible path length
• A Traveling Salesman-type planner to generate a covering set route based on the path length abstraction
• A smooth path generator that provides C2 routes that satisfy user specified curvature constraints
C2 A set of algorithms to coordinate multiple UAVs, including mission commencement
from arbitrary locations to the start of a coordinated mission and de-confliction of
paths to avoid collisions with other vehicles and fixed obstacles
iv
C3 A numerically robust toolbox of spline-based algorithms tailored for vehicle routing
validated through flight test experiments on multiple platforms. A variety of tests
and platforms are discussed.
The algorithms presented are based on a technical approach with approximately equal
emphasis on analysis, computation, dynamic simulation, and flight test experimentation.
Our planner (C1) directly takes into account vehicle maneuverability and agility constraints
that could otherwise render simple solutions infeasible. This is especially important when
surveillance objectives elevate the importance of optimized paths. Researchers have devel
oped a diverse range of solutions for persistent surveillance applications but few directly
address dynamic maneuver constraints.
The key feature of C1 is a two stage sequential solution that discretizes the problem so that
graph search techniques can be combined with parametric polynomial curve generation.
A method to abstract the kino-dynamics of the aerial platforms is then presented so that
a graph search solution can be adapted for this application. An A* Traveling Salesman
Problem (TSP) algorithm is developed to search the discretized space using the abstract
distance metric to acquire more data or avoid obstacles. Results of the graph search are
then transcribed into smooth paths based on vehicle maneuver constraints. A complete
solution for a single vehicle periodic tour of the area is developed using the results of the
graph search algorithm. To execute the mission, we present a simultaneous arrival algorithm
(C2) to coordinate execution by multiple vehicles to satisfy data refresh requirements and
to ensure there are no collisions at any of the path intersections.
We present a toolbox of spline-based algorithms (C3) to streamline the development of C2
continuous paths with numerical stability. These tools are applied to an aerial persistent
surveillance application to illustrate their utility. Comparisons with other parametric poly
nomial approaches are highlighted to underscore the benefits of the B-spline framework.
Performance limits with respect to feasibility constraints are documented
Practical approach to real-time trajectory tracking of UAV formations
Abstract — An Unmanned Aerial Vehicle (UAV) formation in a leader-follower structure, where the UAVs are flying a common trajectory determined by a route planner hosted on the leader is considered. The path description is compressed by polynomial functions with respect to the flight envelope constraints and transmitted to the followers, where a Model Predictive Control (MPC) outer loop controller specifies the command signals for the H ∞ locally controlled dynamics with respect to the nonlinear constraints of the aircraft dynamics. Real time feasibility issues associated with the design are discussed. I
Optimal Trajectory Tracking for an Autonomous UAV
The aim of the present project is the design of optimal flight trajectories for an automomous aerial vehicle which is expected to reach the desired locations in the operational environment expressed in terms of planned waypoints. The navigation must be performed with the vehicle’s best effort, i.e. with the lowest cost. Hence, we want to minimize the input energy, a function of the inputs for the mathematical model which describes the dynamics of the vehicle. The trajectory must satisfy all the constraints and pass through all the planned waypoints. Assuming the vehicle as a point mass model, the best solution has been investigated through a genetic algorithm search procedure. The optimisation problem has been solved by modifying a micro-genetic algorithm software which was initially developed by D.L. Carroll. Between all the possible trajectories we select the more “realistic” connections among the waypoints. First of all, we have left out the trajectories with discontinuity in the derivatives as these are not feasible by the real aircraft. The polynomial spline is a suitable candidate to solve our problem. The algorithm splits the trajectory in sub-trajectories which join a sequence of three waypoints. Starting from the first three waypoints, the following sub-trajectories are superimposed keeping the first waypoint coincident with the last of the previous sub-trajectory. The sequence of polynomials is initialized assuming that jumps in the direction of flight are avoided pointing the heading angle in the presumed direction of flight. The optimal trajectory is a trade-off amongst three factors: the required energy cost, the minimum distance from the required waypoint and the feasibility of the trajectory. Results obtained with this optimization procedure are presented
Path planning and reactive based control for a quadrotor with a suspended load
This paper presents a solution to quadrotor cargo transportation, more precisely when cargo is suspended as a sling load. The challenge lies in payload position control and swing attenuation, which we approach by dividing the model into subsystems: attitude quadrotor in free flight, and translational and attitude load dynamics. We propose a solution based on reactive control, in the sense that we utilize a reactive force that reacts to the error position and the oscillation in the load. Asymptotic stability of the system's closed-loop equilibrium is proved using Lyapunov theory. Additionally, a three-dimensional path planning algorithm is proposed based on cubic splines, which give us a natural path between initial and final desired points. Moreover, we convert the path planning problem into trajectory tracking with a spline's correct parametrization. Control and path planning performance are demonstrated with numerical simulations in three different scenarios
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