Luis Rodolfo García Carrillo

Modeling the Quad-Rotor Mini-Rotorcraft

This chapter presents the modeling of a quad-rotor UAV. A general overview of the quad-rotor helicopter and its operation principle is given. Next, the quad-rotor modeling is addressed using two different approaches: Euler–Lagrange and Newton–Euler. How to derive Lagrange’s equations from Newton’s equations is also shown. Finally, the author presents also the Newton–Euler modeling for an “X-Flyer” quad-rotor configuration.

Distributed infrastructure inspection path planning for aerial robotics subject to time constraints

Within this paper, the problem of 3D inspection path planning for distributed infrastructure using aerial robots that are subject to time constraints is addressed. The proposed algorithm handles varying spatial properties of the infrastructure facilities, accounts for their different importance and exploration function and computes an overall inspection path of high inspection reward while respecting the robot endurance or mission time constraints, as well as the vehicle dynamics and sensor limitations. To achieve its goal, it employs an iterative, 3-step optimization strategy within which it first randomly samples a set of possible structures to visit, subsequently solves the derived traveling salesman problem and computes the travel costs, while finally it randomly assigns inspection times to each structure, and evaluates the total inspection reward. For the derivation of the inspection paths per each independent facility, it interfaces a path planner dedicated to the 3D coverage of single structures. The resulting algorithm properties, computational performance and path quality are evaluated using simulation studies as well as an experimental test-case employing a multirotor micro aerial vehicle.

Adaptive high order sliding mode control for relative positioning and trajectory tracking of spacecraft formation flying

This paper considers the problem of relative position and trajectory tracking control for spacecraft formation flying. The nonlinear dynamics describing the relative positioning of multiple spacecraft are used to develop a Lyapunov-based, nonlinear, adaptive higher order sliding mode control. The strategy, known as adaptive super twisting sliding mode control law, guarantees convergence to any sufficiently smooth desired spacecraft formation flying trajectory, despite the presence of unknown disturbances. Simulation results illustrate the effectiveness of the proposed control.

Advanced Doppler radar physiological sensing technique for drone detection

A 24 GHz medium-range human detecting sensor, using the Doppler Radar Physiological Sensing (DRPS) technique, which can also detect unmanned aerial vehicles (UAVs or drones), is currently under development for potential rescue and anti-drone applications. DRPS systems are specifically designed to remotely monitor small movements of non-metallic human tissues such as cardiopulmonary activity and respiration. Once optimized, the unique capabilities of DRPS could be used to detect UAVs. Initial measurements have shown that DRPS technology is able to detect moving and stationary humans, as well as largely non-metallic multi-rotor drone helicopters. Further data processing will incorporate pattern recognition to detect multiple signatures (motor vibration and hovering patterns) of UAVs.

Distributed Optimal Flocking Design for Multi-agent Two-Player Zero-Sum Games with Unknown System Dynamics and Disturbance

In this paper, distributed flocking strategies have been exploited for multi-agent two-player zero-sum games. Two main challenges are addressed, i.e. (a) handling system uncertainties and disturbances, and (b) achieving optimality. Adopting the emerging Approximate Dynamic Programming (ADP) technology, a novel distributed adaptive flocking design is proposed to optimize the multi-agent two-player zero-sum games even when the system dynamics and disturbances are unknown. First, to evaluate the multi-agent flocking performance and effects from disturbances, a novel flocking cost function is developed. Next, an innovative type of online neural network (NN) based identifier is proposed to approximate the multi-agent zero-sum game system dynamics effectively. Subsequently, another novel neural network (NN) is proposed to approximate the optimal flocking cost function by using the Hamilton-Jacobi-Isaacs (HJI) equation in a forward in time manner. Moreover, a novel additional term is designed and included into the NN update law to relax the stringent requirement of initial admissible control. Eventually, the distributed adaptive optimal flocking design is obtained by using the learnt Multi-agent zero-sum games system dynamics and approximated optimal flocking cost function. Simulation results demonstrate the effectiveness of proposed scheme.

Online UAS local path-planning algorithm for outdoors obstacle avoidance based on attractive and repulsive potential fields

This paper addresses the problem of enabling Unmanned Aircraft Systems (UAS) to avoid mid-air collisions during path planning applications. We propose an improved strategy that allows the UAS to negotiate obstacles encountered during flight, while keeping the objective of finding a feasible path towards its destination. Our method computes multiple steps along the UASs path based on GPS coordinates, a strategy which we refer to as dynamic waypoints generation. When a risk of collision is encountered, new dynamic waypoints are generated by taking into account the obstacles planar coordinates, as well as an approximate circular envelope around it, which allows addressing a most type of obstacles shapes. Real-time experiments performed outdoors with a holonomic UAS are provided, demonstrating the effectiveness and reliability of the proposed strategy.

The Quad-Rotor Experimental Platform

This chapter is devoted to the development of a ground station for supervising the aerial vehicle, as well as the development of three quad-rotor experimental platforms. General details concerning the most common sensing technologies available on UAVs are given, as well as the architecture of this kind of experimental platforms. The quad-rotors conceived during the research activities are described in detail. A hierarchical control strategy is introduced, which allows stabilizing the quad-rotor during autonomous flights. The performances of the vehicles are validated in real-time experiments.

Combining Stereo Imaging, Inertial and Altitude Sensing Systems for the Quad-Rotor

This chapter is devoted to the design and implementation of a stereo-vision, inertial and altitude sensing system for a quad-rotor. The objective is to enable the vehicle to autonomously perform take-off, relative positioning, navigation and landing when evolving in unstructured, indoors, and GPS-denied environments. A real-time comparison study between a Luenberger observer, a Kalman filter and a complementary filter is also addressed, with the purpose of validating the most effective approach for combining the different sensing technologies.

Vision-Based Control of a Quad-Rotor UAV

This chapter introduces two different vision-based control strategies for stabilizing a quad-rotor during flight. The first strategy is based on a homography estimation technique and an optical flow computation. Using this approach, a comparison of three control methods is addressed, with the purpose of validating the most effective approach for stabilizing the vehicle when using visual feedback. In the second strategy, the vision system is implemented for allowing altitude control, which allows stabilizing the 3-dimensional position and regulating the velocity of the vehicle using optical flow. For validating the effectiveness of the two vision-based control strategies, the tasks of autonomous hover and navigation are executed in real-time experiments.

Hovering Flight Improvement

This chapter introduces an embedded control system for improving the attitude stabilization of a quad-rotor. The proposed control strategy uses low cost components and includes an extra control loop based on motor armature current feedback. The control strategy presented here is a controller that is robust with respect to external disturbances. Experimental results for indoor tests are presented to show how this additional control loop improves the performance of the quad-rotor attitude stability.