Hector Garcia de Marina

Adaptive UAV Attitude Estimation Employing Unscented Kalman Filter, FOAM and Low-Cost MEMS Sensors

Navigation employing low cost MicroElectroMechanical Systems (MEMS) sensors in Unmanned Aerial Vehicles (UAVs) is an uprising challenge. One important part of this navigation is the right estimation of the attitude angles. Most of the existent algorithms handle the sensor readings in a fixed way, leading to large errors in different mission stages like take-off aerobatic maneuvers. This paper presents an adaptive method to estimate these angles using off-the-shelf components. This paper introduces an Attitude Heading Reference System (AHRS) based on the Unscented Kalman Filter (UKF) using the Fast Optimal Attitude Matrix (FOAM) algorithm as the observation model. The performance of the method is assessed through simulations. Moreover, field experiments are presented using a real fixed-wing UAV. The proposed low cost solution, implemented in a microcontroller, shows a satisfactory real time performance.

Taming Mismatches in Inter-agent Distances for the Formation-Motion Control of Second-Order Agents

This paper presents the analysis on the influence of distance mismatches on the standard gradient-based rigid formation control for second-order agents. It is shown that, similar to the first-order case as recently discussed in the literature, these mismatches introduce two undesired group behaviors: A distorted final shape and a steady-state motion of the group formation. We show that such undesired behaviors can be eliminated by combining the standard formation control law with distributed estimators. Finally, we show how the mismatches can be effectively employed as design parameters in order to control a combined translational and rotational motion of the formation.

Controlling formation of autonomous agents with distance disagreements

Abstract We address the robustness issue for controlling, using only local information, the shapes of undirected rigid formations of autonomous agents when the agents disagree with their neighboring peers on the prescribed or measured distances between them. We propose to make use of simple local estimators as part of the distributed controllers. It is proved then that for infinitesimally rigid undirected formations satisfying a specific condition determined by the geometric shape of the desired formation and which agents are chosen to estimate the disagreements, our controller locally stabilizes exponentially the formations when the distance disagreements are small. In addition, the formation under control stops moving in the end and does not exhibit any undesirable motion caused by the distance disagreements. The final actual distances between the neighboring agents can be calculated directly from the steady-state values of the estimators. The simulation results for a six-agent formation validates the performance of the proposed controller.

A development project of autonomous marine surface vehicles for sea demining

A sea demining system using autonomous marine surface vehicles (AMSV) is introduced. The research involves the development of exemplars of these vehicles, and the procedures for area scanning and coverage. The demining is made by field influence, towing a submerged “fish”. This study is made both with simulations and with scale experiments.

Guidance algorithm for smooth trajectory tracking of a fixed wing UAV flying in wind flows

This paper presents an algorithm for solving the problem of tracking smooth curves by a fixed wing unmanned aerial vehicle travelling with a constant airspeed and under a constant wind disturbance. The algorithm is based on the idea of following a guiding vector field which is constructed from the implicit function that describes the desired (possibly time-varying) trajectory. The output of the algorithm can be directly expressed in terms of the bank angle of the UAV in order to achieve coordinated turns. Furthermore, the algorithm can be tuned offline such that physical constraints of the UAV, e.g. the maximum bank angle, will not be violated in a neighborhood of the desired trajectory. We provide the corresponding theoretical convergence analysis and performance results from actual flights.

Optimization-based worst-case analysis of a launcher during the atmospheric ascent phase

This article presents the application of optimization-based worst-case search approaches to the VEGA launcher during the P80 ascent phase. Four optimization algorithms are applied covering evolutionary and deterministic global methods as well as their hybrid versions, i.e. mixed with local approaches. A comparison with a traditional Monte Carlo campaign shows that the optimization-based algorithms are much amenable to worst-case search.

Distributed scaling control of rigid formations

Recently it has been reported that biased range-measurements among neighboring agents in the gradient distance-based formation control can lead to predictable collective motion. In this paper we take advantage of this effect and by introducing distributed parameters to the prescribed inter-distances we are able to manipulate the steady-state motion of the formation. This manipulation is in the form of inducing simultaneously the combination of constant translational and angular velocities and a controlled scaling of the rigid formation. While the computation of the distributed parameters for the translational and angular velocities is based on the well-known graph rigidity theory, the parameters responsible for the scaling are based on some recent findings in bearing rigidity theory. We carry out the stability analysis of the modified gradient system and simulations in order to validate the main result.

Sea demining with autonomous marine surface vehicles

A sea demining method using autonomous marine surface vehicles (AMSV) is introduced. The method involves the development of copies of these vehicles, and the procedures for area scanning and coverage. The demining is made by field influence, towing a submerged “fish”. This study is made with both simulations and scale experiments.

Distributed formation tracking using local coordinate systems

Abstract This paper studies the formation tracking problem for multi-agent systems, for which a distributed estimator–controller scheme is designed relying only on the agents’ local coordinate systems such that the centroid of the controlled formation tracks a given trajectory. By introducing a gradient descent term into the estimator, the explicit knowledge of the bound of the agents’ speed is not necessary in contrast to existing works, and each agent is able to compute the centroid of the whole formation in finite time. Then, based on the centroid estimation, a distributed control algorithm is proposed to render the formation tracking and stabilization errors to converge to zero, respectively. Finally, numerical simulations are carried to validate our proposed framework for solving the formation tracking problem.

Quantization effects and convergence properties of rigid formation control systems with quantized distance measurements

In this paper, we discuss quantization effects in rigid formation control systems when target formations are described by interagent distances. Because of practical sensing and measurement constraints, we consider in this paper distance measurements in their quantized forms. We show that under gradient-based formation control, in the case of uniform quantization, the distance errors converge locally to a bounded set whose size depends on the quantization error, while in the case of logarithmic quantization, all distance errors converge locally to zero. A special quantizer involving the signum function is then considered with which all agents can only measure coarse distances in terms of binary information. In this case, the formation converges locally to a target formation within a finite time. Lastly, we discuss the effect of asymmetric uniform quantization on rigid formation control.