Antidio Viguria

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.

SET: An algorithm for distributed multirobot task allocation with dynamic negotiation based on task subsets

The multi-robot task allocation (MRTA) problem has become a key research topic in the field of distributed multirobot coordination in recent years. In this paper, two algorithms for the distributed solution of the MRTA problem are presented. In our market-based approach, robots consider their local plans when bidding and multiple tasks can be allocated to a single robot during the negotiation process. The second algorithm described in the paper is based on the negotiation of subset of tasks and can be considered as a generalization of the first one, which only negotiates single tasks. Both algorithms have been tested in a multirobot simulator with multiple missions consisting in visiting waypoints with promising results.

Distributed Service-Based Cooperation in Aerial/Ground Robot Teams Applied to Fire Detection and Extinguishing Missions

This paper presents a system for the coordination of aerial and ground robots for applications such as surveillance and intervention in emergency management. The overall system architecture is described. An important part for the coordination between robots is the task allocation strategy. A distributed market-based algorithm, called S + T, has been developed to solve the multi-robot task allocation problem in applications that require cooperation among the robots to accomplish all the tasks. Using this algorithm, robots can provide transport and communication relay services dynamically to other robots during the missions. Moreover, the paper presents a demonstration with a team of heterogeneous robots (aerial and ground) cooperating in a mission of fire detection and extinguishing.

An Integrated Approach for Achieving Multirobot Task Formations

In this paper, a problem, called the initial formation problem, within the multirobot task allocation domain is addressed. This problem consists in deciding which robot should go to each of the positions of the formation in order to minimize an objective. Two different distributed algorithms that solve this problem are explained. The second algorithm presents a novel approach that uses cost means to model the cost distribution and improves the performance of the task allocation algorithm. Also, we present an approach that integrates distributed task allocation algorithms with a behavior-based architecture to control formations of robot teams. Finally, simulations and real experiments are used to analyze the formation behavior and provide performance metrics associated with implementation in realistic scenarios.

A multilayer control for multirotor UAVs equipped with a servo robot arm

A multilayer architecture to control multirotor UAVs equipped with a servo robot arm is proposed in this paper. The main purpose is to control the aerial platform taking into account the presence of the moving manipulator. Three layers are considered in this work. First, a novel mechanism is proposed considering a moving battery to counterweight the statics of the robotic arm. Then, in order to overcome the mechanical limitations of the previous layer, the residual of the arm static effects on the UAV is computed and compensated through the given control thrust and torques. Finally, an estimator of external forces and moments acting on the aerial vehicle is considered and the estimations are fed back to the controller to compensate neglected aerodynamic effects and the arm dynamics. The performance of the proposed architecture has been experimentally evaluated.

S+T: An algorithm for distributed multirobot task allocation based on services for improving robot cooperation

In this paper, we present a distributed market-based algorithm called S+T, which solves the multi-robot task allocation (MRTA) problem in applications that require the cooperation among the robots to accomplish all the tasks. If a robot cannot execute a task by itself, it asks for help and, if possible, another robot will provide the required service. In the paper, tasks consisting in transmitting data in real-time that could require communication relay services are considered. On the other hand, the parameters of the algorithm can be adapted to give priority to either the execution time or the energy consumption in the mission. The potential generation of deadlocks associated to the relation between tasks and services is studied, and as an original result, a distributed algorithm that prevent them is proposed. The algorithm has been tested in simulations that illustrate the main features of the S+T algorithm.

Hybrid visual servoing with hierarchical task composition for aerial manipulation

In this letter, a hybrid visual servoing with a hierarchical task-composition control framework is described for aerial manipulation, i.e., for the control of an aerial vehicle endowed with a robot arm. The proposed approach suitably combines into a unique hybrid-control framework the main benefits of both image-based and position-based control schemes. Moreover, the underactuation of the aerial vehicle has been explicitly taken into account in a general formulation, together with a dynamic smooth activation mechanism. Both simulation case studies and experiments are presented to demonstrate the performance of the proposed technique.

Conflict Detection and Resolution Method for Cooperating Unmanned Aerial Vehicles

This paper presents a Conflict Detection and Resolution (CDR) method for cooperating Unmanned Aerial Vehicles (UAVs) sharing airspace. The proposed method detects conflicts using an algorithm based on axis-aligned minimum bounding box and solves the detected conflicts cooperatively using a genetic algorithm that modifies the trajectories of the UAVs with an overall minimum cost. The method changes the initial flight plan of each UAV by adding intermediate waypoints that define the solution flight plan while maintaining their velocities. The method has been validated with many simulations and experimental results with multiple aerial vehicles platforms based on quadrotors in a common airspace. The experiments have been carried out in the multi-UAV aerial testbed of the Center for Advanced Aerospace Technologies (CATEC).

Model-Based Design, Development and Validation for UAS Critical Software

This paper focuses on the major phases present in the development of critical software for UAS: design, development, testing and validation with flying experiments. A model-based approach is the backbone of all these development phases. The presented approach enables the researchers or engineers to work over the whole development cycle with the same tools, and produces an improvement over the classical design cycle. The model-based approach is illustrated with the development of guidance, navigation and control algorithms applied to rotary-wing UAVs. The paper discusses several implementation issues, including the integration of a hardware in the loop (HWIL) test environment within the model-based development cycle. Finally, several simulations and experimental results for this application are shown.

Tether-guided landing of unmanned helicopters without GPS sensors

Landing of unmanned helicopters is a challenging maneuver which can be seriously affected by GPS sensor reliability. This work explores an alternative approach to GPS sensors to avoid typical drawbacks, such as inaccuracies of standalone sensors or weight/cost for Real Time Kinematic (RTK) setups. To this end, the paper studies a setup consisting of a tether linking the helicopter to the landing point. Appropriate sensing of tether attitude relative to the helicopter together with an altitude measurement, allows estimation of the helicopters linear position relative to the landing point. Additionally, the tension exerted on the tether provides a stabilizing effect on helicopter translational dynamics. Taking into account all these considerations, a model-based control strategy is developed and implemented in the real platform. The experimental results endorse the validity of the proposed approach.