Urban air mobility is an innovative mode of transportation in which electric vertical takeoff and landing (eVTOL) vehicles operate between nodes called vertiports. We outline a self-organized vertiport arrival system based on deep reinforcement learning. The airspace around the vertiport is assumed to be circular, and the vehicles can freely operate inside. Each aircraft is considered an individual agent and follows a shared policy, resulting in decentralized actions that are based on local information. We investigate the development of the reinforcement learning policy during training and illustrate how the algorithm moves from suboptimal local holding patterns to a safe and efficient final policy. The latter is validated in simulation-based scenarios and also deployed on small-scale unmanned aerial vehicles to showcase its real-world usability.

As robotic systems such as autonomous cars and delivery drones assume greater roles and responsibilities within society, the likelihood and impact of catastrophic software failure within those systems is increased.To aid researchers in the development of new methods to measure and assure the safety and quality of robotics software, we systematically curated a dataset of 221 bugs across 7 popular and diverse software systems implemented via the Robot Operating System (ROS). We produce historically accurate recreations of each of the 221 defective software versions in the form of Docker images, and use a grounded theory approach to examine and categorize their corresponding faults, failures, and fixes. Finally, we reflect on the implications of our findings and outline future research directions for the community.

Rep. Mike Waltz, R-Fla., and Hoover Institution senior fellow Victor Davis Hanson react to military leaders testifying during House hearing on President Biden's Afghanistan withdrawal on'Hannity.' President Biden's condemnation of the Israeli airstrike that killed seven food aid workers in Gaza earlier this week isn't sitting well with some critics, who called the president's reaction "obvious hypocrisy." Biden responded after the World Central Kitchen (WCK) nonprofit, founded by celebrity chef Jose Andres, announced Tuesday that it was pausing all its operations in Gaza after seven of its food aid workers – including a dual U.S.-Canadian citizen -- were killed by an "unforgivable" Israeli airstrike. "I am outraged and heartbroken by the deaths of seven humanitarian workers from World Central Kitchen, including one American, in Gaza yesterday," Biden wrote in a statement. "They were providing food to hungry civilians in the middle of a war. They were brave and selfless. Their deaths are a tragedy."

Current and former U.S. officials expressed fears on Tuesday that Israel's airstrikes on an Iranian embassy compound in Syria could escalate hostilities in the region, and prompt retaliatory strikes against Israel and its American ally. The officials said the attack on Monday, which killed three generals in Iran's Quds Force and four other officers, had dealt a serious blow to the force, the external military and intelligence service of the Islamic Revolutionary Guards Corps. Ralph Goff, a former senior C.I.A. official who served in the Middle East, called Israel's strike "incredibly reckless." "It will only result in escalation by Iran and its proxies, which is very dangerous" to American troops in the region who could be targeted in retaliatory strikes by Tehran's proxies, Mr. Goff said. Indeed, after the Israeli strike in Damascus, Syria's capital, on Monday, American troops based in southeastern Syria knocked down an attack drone, a Defense Department official said.

Video captures the moment and aftermath of what appears to be a drone, allegedly of Ukrainian origin, striking Russian drone production facility. Russian officials claimed that only a worker's dormitory was hit. A Ukrainian "plane-type UAV" on Tuesday struck a Russian weapons plant that allegedly assembled drones, causing an incredible fireball after impact. "This morning, the republic's industrial enterprises in Yelabuga and Nizhnekamsk were attacked by drones," Rustam Minnikhanov, the leader of Russia's autonomous Republic of Tatarstan, said in a post on his Telegram channel. "There is no serious damage, the technological process of the enterprises was not disrupted," Minnikhanov added.

A suspected Ukrainian drone struck a dormitory in Russia's Tatarstan region – sending fireballs into the air and people scattering. At least 7 people were injured in the attack that struck an industrial part of town, where a factory making Iranian-designed drones is reportedly located.

Russia's top security agency says it has seized dozens of kilos of explosives sent from Ukraine concealed in Orthodox Christian religious icons that had transited through the European Union. The seizure took place on Tuesday, following an inspection of cargo in the northwestern Pskov region near the Latvian border, the Federal Security Service (FSB) said in a statement. There was no immediate comment by Ukraine, which has been fighting off a Russian invasion since February 2022. The FSB said the cargo had passed through Romania, Hungary, Slovakia, Poland, Lithuania and Latvia, and comprised 70 kilos (154 pounds) of home-made explosives and explosive devices "hidden in icons and ready for use". One person was arrested, it continued, adding that it would seek to track down all those involved, including foreigners, who would then face legal proceedings in Russia.

Yelabuga is located in the Alabuga "special economic zone" - an area with a special legal system aimed at attracting foreign investment. Iranian Shahed drones - which are frequently used by Russia to attack Ukraine - are thought to be assembled in Yelabuga.

Despite their growing popularity, swarms of robots remain limited by the operating time of each individual. We present algorithms which allow a human to sculpt a swarm of robots into a shape that persists in space perpetually, independent of onboard energy constraints such as batteries. Robots generate a path through a shape such that robots cycle in and out of the shape. Robots inside the shape react to human initiated changes and adapt the path through the shape accordingly. Robots outside the shape recharge and return to the shape so that the shape can persist indefinitely. The presented algorithms communicate shape changes throughout the swarm using message passing and robot motion. These algorithms enable the swarm to persist through any arbitrary changes to the shape. We describe these algorithms in detail and present their performance in simulation and on a swarm of mobile robots. The result is a swarm behavior more suitable for extended duration, dynamic shape-based tasks in applications such as agriculture and emergency response.

In this article, we explore the potential of zero-shot Large Multimodal Models (LMMs) in the domain of drone perception. We focus on person detection and action recognition tasks and evaluate two prominent LMMs, namely YOLO-World and GPT-4V(ision) using a publicly available dataset captured from aerial views. Traditional deep learning approaches rely heavily on large and high-quality training datasets. However, in certain robotic settings, acquiring such datasets can be resource-intensive or impractical within a reasonable timeframe. The flexibility of prompt-based Large Multimodal Models (LMMs) and their exceptional generalization capabilities have the potential to revolutionize robotics applications in these scenarios. Our findings suggest that YOLO-World demonstrates good detection performance. GPT-4V struggles with accurately classifying action classes but delivers promising results in filtering out unwanted region proposals and in providing a general description of the scenery. This research represents an initial step in leveraging LMMs for drone perception and establishes a foundation for future investigations in this area.