Guillermo Heredia

Control of an aerial robot with multi-link arm for assembly tasks

This paper deals with aerial manipulators consisting of an unmanned aerial vehicle equipped with a robotic multi-link arm. The paper presents methods for the control of the aerial platform taking into account the motion of the arm. It shows how a Variable Parameter Integral Backstepping controller outperforms the results obtained by using PID controllers. The paper presents a quadrotor with a new arm designed for assembly tasks and the implementation of the proposed control methods. Simulations and outdoor experiments confirm the validity of the proposed approach.

Stability analysis of mobile robot path tracking

This paper presents a new approach that analyzes the stability of a general class of path tracking algorithms taking into account the pure delay in the control loop. The analysis has been done for straight paths and paths of constant curvature. This has sufficient generality since most usual paths can be decomposed in pieces of constant curvature. The method has been applied to the pure pursuit path tracking algorithm, one of the most widely used algorithms. The experiments performed with a computer controlled high mobility multi-purpose wheeled vehicle show good agreement with the theoretical predictions of the proposed method.

Multi-Unmanned Aerial Vehicle (UAV) Cooperative Fault Detection Employing Differential Global Positioning (DGPS), Inertial and Vision Sensors.

This paper presents a method to increase the reliability of Unmanned Aerial Vehicle (UAV) sensor Fault Detection and Identification (FDI) in a multi-UAV context. Differential Global Positioning System (DGPS) and inertial sensors are used for sensor FDI in each UAV. The method uses additional position estimations that augment individual UAV FDI system. These additional estimations are obtained using images from the same planar scene taken from two different UAVs. Since accuracy and noise level of the estimation depends on several factors, dynamic replanning of the multi-UAV team can be used to obtain a better estimation in case of faults caused by slow growing errors of absolute position estimation that cannot be detected by using local FDI in the UAVs. Experimental results with data from two real UAVs are also presented.

Control of a multirotor outdoor aerial manipulator

This paper presents the design and control of a multirotor-based aerial manipulator developed for outdoor operation. The multi-rotor has eight rotors and large payload to integrate a 7-degrees of freedom arm and to carry sensors and processing hardware needed for outdoor positioning. The arm can also carry an end-effector and sensors to perform different missions. The paper focuses on the control design and implementation aspects. A stable backstepping-based controller for the multirotor that uses the coupled full dynamic model is proposed, and an admittance controller for the manipulator arm is outlined. Several experimental tests with the aerial manipulator are also presented. In one of the experiments, the performance of the pitch attitude controller is compared to a PID controller. Other experiments of the arm controller following an object with the camera are also presented.

Detection of Sensor Faults in Autonomous Helicopters

This paper presents a sensor fault detection and diagnosis system for autonomous helicopters. The system has been tested with the MARVIN autonomous helicopter. Fault detection is accomplished by evaluating any significant change in the behaviour of the vehicle with respect to the fault-free behaviour, which is estimated by using an observer. The effectiveness of the proposed approach is demonstrated by means of MARVIN experimental results.

Sensor fault detection in small autonomous helicopters using observer/Kalman filter identification

This paper presents a sensor fault detection and diagnosis system for small autonomous helicopters. Fault detection is accomplished by evaluating any significant change in the behaviour of the vehicle with respect to the fault-free behaviour, which is estimated by using an observer. The observer is obtained from input-output experimental data with the observer/Kalman filter identification method. The system is tested with real helicopter flight data.

Control and perception components for autonomous vehicle guidance. Application to the ROMEO vehicles

Abstract This paper presents several control and perception components that implement navigation behaviours in autonomous vehicles. A behaviour-based control architecture integrating these components is also presented. The paper concentrates on autonomous tracking behaviours. In particular, the tracking of explicit paths, moving targets and environmental features are described. These behaviours have been implemented using several different position estimation techniques: dead reckoning; global position estimation using GPS; and position estimation with respect to the environment. The control architecture has been implemented in ROMEO vehicles at the University of Seville. These autonomous vehicles are adaptated from conventional electric vehicles and are currently used for experiments in autonomous navigation and teleoperation in outdoor environments. A short description of the general characteristics of the ROMEO-3R (tricycle) and ROMEO-4R (four wheels) vehicles is presented. The paper includes results from the tracking of environmenal features with proximity sensors, and visual tracking of moving targets.

Virtual Sensor for Failure Detection, Identification and Recovery in the Transition Phase of a Morphing Aircraft

The Helicopter Adaptive Aircraft (HADA) is a morphing aircraft which is able to take-off as a helicopter and, when in forward flight, unfold the wings that are hidden under the fuselage, and transfer the power from the main rotor to a propeller, thus morphing from a helicopter to an airplane. In this process, the reliable folding and unfolding of the wings is critical, since a failure may determine the ability to perform a mission, and may even be catastrophic. This paper proposes a virtual sensor based Fault Detection, Identification and Recovery (FDIR) system to increase the reliability of the HADA aircraft. The virtual sensor is able to capture the nonlinear interaction between the folding/unfolding wings aerodynamics and the HADA airframe using the navigation sensor measurements. The proposed FDIR system has been validated using a simulation model of the HADA aircraft, which includes real phenomena as sensor noise and sampling characteristics and turbulence and wind perturbations.

ACTUATOR FAULT DETECTION IN AUTONOMOUS HELICOPTERS

Abstract This paper presents an actuator fault detection and diagnosis system for autonomous helicopters. The system has been tested with the MARVIN autonomous helicopter. Fault detection is accomplished by evaluating any significant change in the behaviour of the vehicle with respect to the fault-free behaviour, which is estimated by using an observer. The effectiveness of the proposed approach is demonstrated by means of MARVIN experimental results and simulations.

Collision-Free 4D Trajectory Planning in Unmanned Aerial Vehicles for Assembly and Structure Construction

This paper presents a new system for assembly and structure construction with multiple Unmanned Aerial Vehicles (UAVs) which automatically identifies conflicts among them. The system proposes the most effective solution considering the available computation time. After detecting conflicts between UAVs, the system resolves them cooperatively using a collision-free 4D trajectory planning algorithm based on a simple one-at-a-time strategy to quickly compute a feasible but non-optimal initial solution and a stochastic optimization technique named Particle Swarm Optimization (PSO) to improve the initial solution. An anytime approach using PSO is applied. It yields trajectories whose quality improves when available computation time increases. Thus, the method could be applied in real-time depending on the available computation time. The method has been validated with simulations in scenarios with multiple UAVs in a common workspace and experiment in an indoor testbed.