This paper presents a method for trajectory generation with Bézier curves, by considering the wind field and dynamic constraints for small Unmanned Aerial Systems (UAS). Atmospheric phenomena affect UAS trajectories, so the wind presence should be considered in order efficiently perform a mission. These missions require precise area decomposition, efficient waypoint sequencing, and a smooth trajectory generation to fulfill the required level of safety and reliability. In this context, a path planning algorithm is presented which incorporates the use of an area decomposition scheme which considers complex shapes and restrictions, in order to provide high levels of coverage. A novel trajectory generation algorithm is proposed, which aims to harvest energy from the atmosphere by taking advantage of the previously estimated wind field and the identified wind features, such as shear wind and discrete gusts, by taking into account flight envelope restrictions. Different test cases and scenarios, including Software-In-The-Loop (SITL) simulations and real telemetry data analysis, are presented to assess the energy gain for the implemented algorithms. The results indicate promising energy gains of almost 15% in voltage saving if the mentioned factors are considered to re-plan the path with the energy-efficient trajectories.

This paper addresses a synchronization problem that arises when a team of robots needs to communicate while repeatedly performing assigned tasks in a cooperative scenario. Each robot has a limited communication range and moves along a previously defined closed trajectory. When two robots are close enough, a communication link may be established, allowing the robots to exchange information. The goal is to schedule the motions such that the entire system can be synchronized for maximum information exchange; that is, every pair of neighbors always visit the feasible communication link at the same time. An algorithm for scheduling the team of robots in this scenario is proposed and a robust framework that assures the synchronization of a large team of robots is presented. Simulations, experiments, and computational results demonstrate the applicability of the algorithm. The approach allows the design of fault-tolerant systems that can be used for multiple tasks, such as surveillance, area exploration, and searching for targets in hazardous environments, among others.

This paper addresses a synchronization problem that arises when a team of aerial robots (ARs) need to communicate while performing assigned tasks in a cooperative scenario. Each robot has a limited communication range and flies within a previously assigned closed path. When two robots are close enough, a communication link may be established allowing the robots to share information. The goal is to schedule the flights such that the entire system can be synchronized for maximum information exchange, that is, every pair of neighbors are on the feasible communication link at the same time. We propose an algorithm for scheduling a team of robots in this scenario and propose a robust framework where the synchronization of a large team of robots is assured. The approach allows us to design a fault-tolerant system that can be used for multiple tasks such as surveillance, area exploration, searching for targets in a hazardous environment, and assembly and structure construction, to name a few.

This paper addresses the area surveillance problem with a team of multiple aerial robots under communication constraints. In previous work of authors [1], a decentralized modular architecture was proposed for surveillance missions with a team of homogeneous robots. This paper presents a decentralized decision-making algorithm that solves the problem for heterogeneous aerial robots with different sensing and motion capabilities. The proposed frequency-based approach offers a dynamic and robust solution able to adapt to changes in the area size and robot capabilities, and even to total robot failures. The algorithm can run properly under communication constraints and there is no robot which rules the others. Simulations and experimental results validate the proposed system for heterogeneous robots that can be dynamically added/removed during the execution of the mission.

This paper presents a new approach for aerial robots simultaneous localization and mapping (SLAM) oriented to aerial manipulation applications. The approach is based on the integration of range-only measurements and visual markers detected with the on-board camera. A multiple hypotheses framework is applied for range-only together with visual markers SLAM. This approach allows integrating two different types of sensors that are complementary for localization, mixing the stable and continuous estimation provided by range sensors with the precise but infrequent measurements from the visual markers. Real experiments involving an aerial robot and radio/visual markers have been used to validate the approach.

This paper presents the perimeter surveillance problem using a set of cooperative robots with heterogeneous speed capabilities under communication constraints. The problem is solved using a frequency-based approach. In the proposed path-partition strategy, the robots patrol a segment length related to their own capabilities and interchanges information with its neighbors periodically. An efficient decentralized algorithm is applied to coordinate the robots from local information and decisions. Finally, simulation and experimental results are presented to illustrate the convergence and the robustness of the solution.

This paper presents an undelayed range-only simultaneous localization and mapping (RO-SLAM) based on the Extended Kalman filter. The approach is optimized for working in 3D scenarios, reducing the required computational payload at two levels: first, using a reduced spherical state vector parametrization and, second, proposing a new EKF update scheme. The paper proposes a state vector parametrization based on Gaussian-Mixture to cope with the multi-modal nature of range-only measurements and a reduced spherical parametrization of the range sensor positions that allows to shorten the length of the state vector for a given number of hypotheses. The approach is firstly tested and discussed in simulation, followed by experimental results involving a real robot and radio-based range sensors.

This paper and video are devoted to the last experiments and demonstration of the AWARE project (European Commission, FP6) carried out in Utrera, near Seville (Spain) May, 2009. The project has developed and validated in field experiments a platform providing the functionalities required for the cooperation of aerial robots with ground sensor-actuator wireless networks, including static and mobile nodes carried by people and vehicles. The project demonstrated the self-deployment, self-configuration and self-repairing of the network by using autonomous helicopters that transported and deployed sensor nodes and loads. These features are highly relevant in natural and urban environments without pre-existing infrastructure or where the infrastructure has been damaged or destroyed. Two validation scenarios have been considered: Disaster Management/Civil Security and Filming.

This paper presents a new method for the 3D localization of an outdoor wireless sensor network (WSN) by using a single flying beacon-node on-board an autonomous helicopter, which is aware of its position thanks to a GPS device. The technique is based on particle filtering and does not require any prior information about the position of the nodes to be estimated. Its structure and stochastic nature allows a distributed computation of the position of the nodes. The paper shows how the method is very suitable for outdoor applications with robotic data-mule systems. The paper includes a section with experiments.

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.

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.

Presents a method to design fuzzy logic controllers of autonomous articulated vehicles. The method considers manoeuvres in industrial environments, including backing-up manoeuvres where the angle between the longitudinal axis of a tractor and its trailer takes large values. These manoeuvres are particularly dangerous because the vehicle can reach the so-called "jackknife" position, which is a very dangerous situation because it may cause the destruction of the roller. Stability analysis is a crucial issue in the backing-up manoeuvres of articulated vehicles. However, the existing results on the stability of fuzzy control systems of articulated vehicles are based on the assumption of a small value of the above-mentioned angle, which is not usually the case when manoeuvring in factories. The paper shows how a fuzzy control system which, under this assumption, satisfies the Lyapunov stability criterion, can lead the system to the "jackknife" position. The method proposed in the paper is based on the qualitative theory of nonlinear dynamical systems and does not assume a small angle between the tractor and the trailer. The paper shows how the method guarantees absolute stability of the fuzzy control system and can preclude the "jackknife" position.