Gerardo Flores

Tracking a Ground Moving Target with a Quadrotor Using Switching Control

An unmanned aerial vehicle (UAV) stabilization strategy based on computer vision and switching controllers is proposed. The main goal of this system is to perform tracking of a moving target on ground. The architecture implemented consists of a quadrotor equipped with an embedded camera which provides real-time video to a computer vision algorithm where images are processed. A vision-based estimator is proposed, which makes use of 2-dimensional images to compute the relative 3-dimensional position and translational velocity of the UAV with respect to the target. The proposed estimator provides the required states measurements to a micro-controller for stabilizing the vehicle during flight. The control strategy consists of switching controllers, which allows making decisions when the target is lost temporarily or when it is out of the camera’s field of view. Real time experiments are presented to demonstrate the performance of the target-tracking system proposed.

Quad-Tilting Rotor Convertible MAV: Modeling and Real-Time Hover Flight Control

This paper describes the modeling, control and hardware implementation of an experimental tilt-rotor aircraft. This vehicle combines the high-speed cruise capabilities of a conventional airplane with the hovering capabilities of a helicopter by tilting their four rotors. Changing between cruise and hover flight modes in mid-air is referred to transition. Dynamic model of the vehicle is derived both for vertical and horizontal flight modes using Newtonian approach. Two nonlinear control strategies are presented and evaluated at simulation level to control, the vertical and horizontal flight dynamics of the vehicle in the longitudinal plane. An experimental prototype named Quad-plane was developed to perform the vertical flight. A low-cost DSP-based Embedded Flight Control System (EFCS) was designed and built to achieve autonomous attitude-stabilized flight.

A Vision and GPS-Based Real-Time Trajectory Planning for a MAV in Unknown and Low-Sunlight Environments

In this paper we address the problem of real-time optimal trajectory generation of a micro Air Vehicle (MAV) in unknown and low-sunlight environments. The MAV is required to navigate from an initial and outdoor position to a final position inside of a building. In order to achieve this goal, the MAV must estimate a window of the building. For this purpose, we develop a safe path planning method using the information provided by the GPS and a consumer depth camera. With the aim of developing a safe path planning with obstacle avoidance capabilities, a model predictive control approach is developed, which uses the environment information acquired by the navigation system. The results are tested on simulations and some preliminary experimental results are given. Our system’s ability to identify and estimate a window model and the relative position w.r.t. the window is demonstrated through video sequences collected from the experimental platform.

Transition flight control of the quad-tilting rotor convertible MAV

This paper presents a model of a particular class of a convertible MAV with fixed wings. This vehicle can operate as a helicopter as well as a conventional airplane, i.e. the aircraft is able to switch their flight configuration from hover to level flight and vice versa by means of a transition maneuver. The paper focuses on finding a controller capable of performing such transition via the tilting of their four rotors. The altitude should remain on a predefined value throughout the transition stage. For this purpose a nonlinear control strategy based on saturations and Lyapunov design is given. The use of this control law enables to make the transition maneuver while maintaining the aircraft in flight. Numerical results are presented, showing the effectiveness of the proposed methodology to deal with the transition stage.

Lyapunov-based controller using singular perturbation theory: An application on a mini-UAV

In this paper, a Lyapunov-based control using singular perturbation theory is proposed and applied on dynamics of a miniature unmanned aerial vehicle (MAV). Such controller is designed taking into account the presence of the small parameter ∈ on vehicle dynamics, causing a time-scale separation between the attitude and translational dynamics of the MAV. The stability analysis is demonstrated by presenting a scenario in which the time-scale property arises on the the MAV dynamics. In addition, the values of the parameter ∈ for which the control law is validated, are given. Simulations are derived an presented to demonstrate the effectiveness of the control law. The proposed controller has been applied to a Quad-plane MAV experimental platform, in order to validate the performance and to show the time-scale property.

Quad-rotor switching control: An application for the task of path following

The problem of vision-based road following using a quad-rotor is addressed. The objective consists of estimating and tracking a road without a priori knowledge of such path. For this purpose, two operational regions are defined: one for the case when the road is detected, and the other one for when it is not. A switching between imaging and inertial sensors measurements allows estimating the required vehicles parameters in both regions. Also, for dealing with both aforementioned cases, a switching control strategy which stabilizes the vehicles lateral position is proposed. The performance of the proposed switching methodologies is tested in real time experiments.

A nonlinear path-following strategy for a fixed-wing MAV

In this paper, a Lyapunov-based control law is developed to steer a fixed-wing mini aerial vehicle (MAV) along a desired path. The proposed controller overcomes stringent initial condition constraints that are present in several path following strategies in the literature. The key idea behind the proposed strategy, is to minimize the error of the path-following trajectory by using a virtual particle, which should be tracked along the path. For this purpose, the particle speed is controlled, providing an extra degree of freedom. Controller design is stated by using Lyapunov techniques. The resulting control strategy yields global convergence of the current path of the MAV to the desired path. Simulations are presented using the simulator MAV3DSim, in order to demonstrate the effectiveness of the control law. Furthermore an experimental platform called MINAVE I is introduced.

Dubins path generation for a fixed wing UAV

A path generator is proposed for a fixed-wing Unmaned Aereal Vehicle (UAV). Assuming that the vehicle maintain a constant altitude, and airspeed, and that the UAV is constrained by a turning rate. The Dubins paths serve as a strategy to find the shortest path for the non-holonomic model of the UAV. Dubins paths consist of three path segments which are based on straight lines or arcs of circle of a given radius. The Dubins path generation is combined with a nonlinear Lypaunov-based path-following control. Finally we present a complete simulation environment in which the path generator and path following strategy are validated. As an example of application we propose the scenario in which a missing person is located in some known area and we use the path generator along with this path-following strategy applied to the fixed wing UAV to search and find this person.

PID switching control for a highway estimation and tracking applied on a convertible mini-UAV

This paper reports current work on development and navigation control of an experimental prototype of a new tilt-rotor convertible aircraft (Quad-plane Mini Unmanned Aerial Vehicle). The goal of the work consists of estimating and tracking a road using a vision system, without any previous knowledge of the road, as well as developing an efficient controller for treat with situations when the road is not detected by the vision sensor. For dealing with this situation, we propose a switching control strategy applied in two operational regions: road detected and no road detected. The exponential stability is proved for the subsystem formed by the lateral position taking into account the switching boundaries between the operational regions. The control law is validated in the proposed platform, showing the expected behavior during autonomous navigation.

A vision and GPS-based real-time trajectory planning for MAV in unknown urban environments

This paper addresses the issue of real-time optimal trajectory generation of a micro Air Vehicle (MAV) in unknown urban environments. The MAV is required to navigate from an initial and outdoor position to a final position inside a building. To achieve this objective, we develop a safe path planning method using the information provided by the GPS and a consumer depth camera. With the purpose to develop a safe path planning with obstacle avoidance capabilities, a model predictive control approach is developed, which uses the environment information acquired by the navigation system.