A framework for computing feasible and constrained trajectories for a fleet of quad-rotors leveraging on Signal Temporal Logic (STL) specifications for power line inspection tasks is proposed in this paper. The planner allows the formulation of complex missions that avoid obstacles and maintain a safe distance between drones while performing the planned mission. An optimization problem is set to generate optimal strategies that satisfy these specifications and also take vehicle constraints into account. Further, an event-triggered replanner is proposed to reply to unforeseen events and external disturbances. An energy minimization term is also considered to implicitly save quad-rotors battery life while carrying out the mission. Numerical simulations in MATLAB and experimental results show the validity and the effectiveness of the proposed approach, and demonstrate its applicability in real-world scenarios.

Personal use of this material is permitted. Abstract-- This paper presents a multi-layer software architecture to perform cooperative missions with a fleet of quadrotors providing support in electrical power line inspection operations. The proposed software framework guarantees the compliance with safety requirements between drones and human workers while ensuring that the mission is carried out successfully. Besides, cognitive capabilities are integrated in the multi-vehicle system in order to reply to unforeseen events and external disturbances. The feasibility and effectiveness of the proposed architecture are demonstrated by means of realistic simulations.

Multi-rotor Unmanned Aerial Vehicles (UAVs) need to tilt in order to move; this modifies the UAV's antenna orientation. We consider the scenario where a multi-rotor UAV serves as a communication relay between a Base Station (BS) and another UAV. We propose a framework to generate feasible trajectories for the multi-rotor UAV relay while considering its motion dynamics and the motion-induced changes of the antenna orientation. The UAV relay's trajectory is optimized to maximize the end-to-end number of bits transmitted. Numerical simulations in MATLAB and Gazebo show the benefits of accounting for the antenna orientation variations due to the UAV tilt.

A software architecture aimed at coordinating a team of heterogeneous aerial vehicles for inspection and maintenance operations in high-voltage power line scenarios is presented in this paper. A hierarchical approach deals with high-level tasks by planning and executing complex missions requiring vehicles to support human operators. A resource-constrained problem allows distributing tasks among the team taking into account vehicles' capabilities and battery constraints. Besides, Behavior Trees (BTs) are in charge of mission execution, triggering replanning operations in case of unforeseen events, such as vehicle faults or communication drop-outs. The feasibility and validity of the approach are showcased through realistic simulations achieved in Gazebo.

A novel prize-winner algorithm designed for a path following problem within the Unmanned Aerial Vehicle (UAV) field is presented in this paper. The proposed approach exploits the advantages offered by the pure pursuing algorithm to set up an intuitive and simple control framework. A path fora quad-rotor UAV is obtained by using downward facing camera images implementing an Image-Based Visual Servoing (IBVS) approach. Numerical simulations in MATLAB together with the MathWorks Virtual Reality (VR) toolbox demonstrate the validity and the effectiveness of the proposed solution. The code is released as open-source making it possible to go through any part of the system and to replicate the obtained results.

This paper presents a family of autonomous Unmanned Aerial Vehicles (UAVs) platforms designed for a diverse range of indoor and outdoor applications. The proposed UAV design is highly modular in terms of used actuators, sensor configurations, and even UAV frames. This allows to achieve, with minimal effort, a proper experimental setup for single, as well as, multi robot scenarios. Presented platforms are intended to facilitate the transition from simulations, and simplified laboratory experiments, into the deployment of aerial robots into uncertain and hard-to-model real-world conditions. We present mechanical designs, electric configurations, and dynamic models of the UAVs, followed by numerous recommendations and technical details required for building such a fully autonomous UAV system for experimental verification of scientific achievements. To show strength and high variability of the proposed system, we present results of tens of completely different real-robot experiments in various environments using distinct actuator and sensory configurations.

In recent years, reinforcement learning and its multi-agent analogue have achieved great success in solving various complex control problems. However, multi-agent reinforcement learning remains challenging both in its theoretical analysis and empirical design of algorithms, especially for large swarms of embodied robotic agents where a definitive toolchain remains part of active research. We use emerging state-of-the-art mean-field control techniques in order to convert many-agent swarm control into more classical single-agent control of distributions. This allows profiting from advances in single-agent reinforcement learning at the cost of assuming weak interaction between agents. However, the mean-field model is violated by the nature of real systems with embodied, physically colliding agents. Thus, we combine collision avoidance and learning of mean-field control into a unified framework for tractably designing intelligent robotic swarm behavior. On the theoretical side, we provide novel approximation guarantees for general mean-field control both in continuous spaces and with collision avoidance. On the practical side, we show that our approach outperforms multi-agent reinforcement learning and allows for decentralized open-loop application while avoiding collisions, both in simulation and real UAV swarms. Overall, we propose a framework for the design of swarm behavior that is both mathematically well-founded and practically useful, enabling the solution of otherwise intractable swarm problems.

Fox News Flash top headlines are here. Check out what's clicking on Foxnews.com. Firefighters worked for a second day Wednesday to fully extinguish a blaze at a U.S. company's drone plant in Latvia. Local police said nothing had been found so far to indicate sabotage. Latvia's State Fire and Rescue Service was alerted Tuesday afternoon that a fire had broken out at Edge Autonomy's drone production plant in Marupe, a town that borders the capital, Riga. The Baltic News Service said that although the blaze was largely contained by 7 p.m. on Tuesday, firefighters continued work to fully extinguish the fire early Wednesday.\

This new technology has evident social and economic impacts on our lifestyle and represents one of the most vital future trends [16]. In this context, Suab et al. have generally explained how different UAVs could be employed in forests and farming [7]. On the other hand, the mobility and flexibility of UAVs as well as their cheap costs represent their most powerful features for developing a new generation of cellular communication flying terminals as in [8][9][10], acquiring images rich of details for executing several geological applications as suggested in [11], or monitoring and tracking wildlife features [12]. Many engineers and researchers look at commercial multicopters as practical devices that could be adapted to perform a wide range of applications, even though they are unable to carry considerable payloads, and their batteries may sustain up to two successive flying hours if their maximal weight, including their payload, is around ten kilos. In such a case, building advanced types of flying robots that satisfy any special requirements regarding their payload or their maximal flying range requires new creative ideas. This paper presents a few novel designs with many technical details including computer vision systems and some modern AI-based algorithms that are required to perform smart missions. The organization of this paper is as follows: first, we present several recently designed and presented platforms for serving in different areas.

Tehran, Iran – Iran's army has unveiled a major underground base to showcase its aerial military capabilities in response to significant joint exercises by the United States and Israel. State television on Tuesday showed footage of a variety of fighter jets and military drones at the base, dubbed the "Eagle 44", the location of which remains unknown. It said the base is dug in the mountains to protect it from ammunition dropped from US strategic bombers that are capable of penetrating defences. The unveiling, which was attended by top military officials, comes less than two weeks after the US and Israel held their largest-ever joint drill, using thousands of troops and dozens of aircraft in addition to naval vessels and artillery systems in what was widely seen as a message to Iran amid rising tensions. That joint drill had in turn come days after Iran held wide-ranging exercises to showcase its military readiness.