A crucial technology in fully autonomous aerial swarms is collaborative SLAM (CSLAM), which enables the estimation of relative pose and global consistent trajectories of aerial robots. However, existing CSLAM systems do not prioritize relative localization accuracy, critical for close collaboration among UAVs. This paper presents $D^2$SLAM, a novel decentralized and distributed ($D^2$) CSLAM system that covers two scenarios: near-field estimation for high accuracy state estimation in close range and far-field estimation for consistent global trajectory estimation. $D^2$SLAM has a versatile and powerful front-end that can use stereo cameras or omnidirectional cameras as input, the former being easy to obtain and the latter being an excellent solution to the Field of View problem in relative localization. Our experiments verify $D^2$SLAM achieves high accuracy in ego-motion estimation, relative localization, and global consistency. Moreover, distributed optimization algorithms are adopted to achieve the $D^2$ objective to allow the scale-up of the swarm and ensure robustness against network delays. We argue $D^2$SLAM can be applied in a wide range of real-world applications.

New emerging technologies powered by Artificial Intelligence (AI) have the potential to disruptively transform our societies for the better. In particular, data-driven learning approaches (i.e., Machine Learning (ML)) have been a true revolution in the advancement of multiple technologies in various application domains. But at the same time there is growing concern about certain intrinsic characteristics of these methodologies that carry potential risks to both safety and fundamental rights. Although there are mechanisms in the adoption process to minimize these risks (e.g., safety regulations), these do not exclude the possibility of harm occurring, and if this happens, victims should be able to seek compensation. Liability regimes will therefore play a key role in ensuring basic protection for victims using or interacting with these systems. However, the same characteristics that make AI systems inherently risky, such as lack of causality, opacity, unpredictability or their self and continuous learning capabilities, may lead to considerable difficulties when it comes to proving causation. This paper presents three case studies, as well as the methodology to reach them, that illustrate these difficulties. Specifically, we address the cases of cleaning robots, delivery drones and robots in education. The outcome of the proposed analysis suggests the need to revise liability regimes to alleviate the burden of proof on victims in cases involving AI technologies. This article appears in the AI & Society track.

Fox News Flash top headlines are here. Check out what's clicking on Foxnews.com. The Belarusian government is struggling to thwart an internal guerrilla group that opposes Minsk's assistance to Russia and has engaged in a sabotage campaign since the war in Ukraine kicked off. Earlier this week, opposition activists from the Association of Security Forces of Belarus (BYPOL), a group formed following the 2020 political turmoil in Belarus, attacked a Russian warplane outside the capital city using drones. "Belarusians will not allow the Russians to freely use our territory for the war with Ukraine, and we want to force them to leave," one retired Belarusian serviceman, who joined a group of saboteurs and goes by the name Anton, told The Associated Press in a report Friday.

The paper proposes two control methods for performing a backflip maneuver with miniature quadcopters. First, an existing feedforward control approach is improved by finding the optimal sequence of motion primitives via Bayesian optimization, using a surrogate Gaussian Process model. To evaluate the cost function, the flip maneuver is performed repeatedly in a simulation environment. The second method is based on closed-loop control and it consists of two main steps: first a novel robust, adaptive controller is designed to provide reliable reference tracking even in case of model uncertainties. The controller is constructed by augmenting the nominal model of the drone with a Gaussian Process that is trained by using measurement data. Second, an efficient trajectory planning algorithm is proposed, which designs feasible trajectories for the flip maneuver by using only quadratic programming. The two approaches are analyzed in simulations and in real experiments using Bitcraze Crazyflie 2.1 quadcopters.

Lt. Gen. Keith Kellogg says China is an adversary, not a competitor, amid growing concerns over rising threats on "Your World." The U.S. Treasury Department announced new sanctions Thursday on a China-based network that sells aerospace components to Iran for manufacturing drones. The Iran Aircraft Manufacturing Industrial Company manufactures the Shahed-136 drones and exports them to Russia, which has increasingly used them to bombard Ukraine in recent months. "Iran is directly implicated in the Ukrainian civilian casualties that result from Russia's use of Iranian UAVs (unmanned aerial vehicle), in Ukraine," said Brian Nelson, the Treasury Department's undersecretary for Terrorism and Financial Intelligence, in a statement on Thursday. "The United States will continue to target global Iranian procurement networks that supply Russia with deadly UAVs for use in its illegal war in Ukraine."

Ridesharing is convenient in part because there's often a vehicle near you, and Alphabet's Wing wants to extend that advantage to drone delivery. The company is debuting a Wing Delivery Network platform that relies on decentralized and highly automated pickups. Drones charge and deliver in whatever locations make the most sense for the broader system. If demand surges in a given area, more drones can operate around the nearest pads. Crucially, your local restaurant or store doesn't have to do much to take advantage of the network.

Fox News chief national security correspondent Jennifer Griffin has the details from the Pentagon on'America Reports.' The United States may have shot down one of Communist China's spy balloons, but America's problem of surveillance from foreign powers is far from destroyed. Many Americans were alarmed as we watched the Biden administration take a dangerously lazy approach to taking down the Chinese spy balloon. We are right to be upset about this, and demand action in response, but that balloon is just a small piece of Communist China's massive surveillance effort targeting you, our military and American businesses. The harsh reality is that the Chinese Communist Party has been surveilling the United States for years using drones purchased with your taxpayer dollars and operated by your federal government.

Fox News Flash top headlines are here. Check out what's clicking on Foxnews.com. An explosion in eastern Syria on Wednesday killed at least three people, according to reports. A war monitoring group said the blast was likely caused by a drone strike that targeted Iran-backed militiamen. No group claimed responsibility for an attack in the area and reports about what had happened were sketchy.

Unmanned aerial vehicle (UAV) tracking is crucial for autonomous navigation and has broad applications in robotic automation fields. However, reliable UAV tracking remains a challenging task due to various difficulties like frequent occlusion and aspect ratio change. Additionally, most of the existing work mainly focuses on explicit information to improve tracking performance, ignoring potential interframe connections. To address the above issues, this work proposes a novel framework with continuity-aware latent interframe information mining for reliable UAV tracking, i.e., ClimRT. Specifically, a new efficient continuity-aware latent interframe information mining network (ClimNet) is proposed for UAV tracking, which can generate highly-effective latent frame between two adjacent frames. Besides, a novel location-continuity Transformer (LCT) is designed to fully explore continuity-aware spatial-temporal information, thereby markedly enhancing UAV tracking. Extensive qualitative and quantitative experiments on three authoritative aerial benchmarks strongly validate the robustness and reliability of ClimRT in UAV tracking performance. Furthermore, real-world tests on the aerial platform validate its practicability and effectiveness. The code and demo materials are released at https://github.com/vision4robotics/ClimRT.

Belarus has detained several people over what it calls an attempted act of sabotage at a Belarusian airfield, President Alexander Lukashenko was cited as saying. Belarusian anti-government activists said last month that they had blown up a sophisticated Russian military aircraft – a Beriev A-50 surveillance plane – in a drone attack at an airfield near the Belarusian capital Minsk, a claim disputed by Moscow and Minsk. "To date, more than 20 accomplices who are in Belarus have been detained. The rest are hiding," said Lukashenko, a key Kremlin ally, according to state news agency Belta. He identified the presumed main culprit as a dual national of Ukraine and Russia.