Early Monday morning, as families were preparing to start their week, waves of explosive drones struck Ukraine's capital. The blasts echoed across Kyiv, setting buildings ablaze and sending people scurrying to shelters. At least three people were killed. Exactly how many drones were used in the attack on the capital was not immediately clear. According to the Associated Press, the drones appeared to include Iranian-made Shaheds, though Iran's government has denied this.

You might suppose Hollywood is good at predicting the future. Indeed, Robert Wallace, head of the CIA's Office of Technical Service and the US equivalent of MI6's fictional Q, has recounted how Russian spies would watch the latest Bond movie to see what technologies might be coming their way. Hollywood's continuing obsession with killer robots might therefore be of significant concern. The newest such movie is Apple TV's forthcoming sex robot courtroom drama Dolly. I never thought I'd write the phrase "sex robot courtroom drama", but there you go.

Russian-launched "kamikaze drones" attacked Kyiv early Monday, the Ukrainian presidency said, describing the strikes as an act of desperation nearly eight months into a war that has claimed thousands of lives. Air raid sirens sounded in Kyiv shortly before the first explosion at around 6:35 am (0335), followed by sirens across most of the country. "The capital was attacked by kamikaze drones," the president's chief of staff Andriy Yermak said on social media. "The Russians think it will help them, but it shows their desperation," he added. "We need more air defence systems and as soon as possible. More weapons to defend the sky and destroy the enemy."

Russian President Vladimir Putin said the strikes last week were in retaliation for the bombing of a key bridge linking Russia to occupied Crimea, which he blamed on Ukraine.

You might suppose Hollywood is good at predicting the future. Indeed, Robert Wallace, head of the CIA's Office of Technical Service and the US equivalent of MI6's fictional Q, has recounted how Russian spies would watch the latest Bond movie to see what technologies might be coming their way. Hollywood's continuing obsession with killer robots might therefore be of significant concern. The newest such movie is Apple TV's forthcoming sex robot courtroom drama Dolly. I never thought I'd write the phrase "sex robot courtroom drama", but there you go.

For real-world applications, autonomous mobile robotic platforms must be capable of navigating safely in a multitude of different and dynamic environments with accurate and robust localization being a key prerequisite. To support further research in this domain, we present the INSANE data sets - a collection of versatile Micro Aerial Vehicle (MAV) data sets for cross-environment localization. The data sets provide various scenarios with multiple stages of difficulty for localization methods. These scenarios range from trajectories in the controlled environment of an indoor motion capture facility, to experiments where the vehicle performs an outdoor maneuver and transitions into a building, requiring changes of sensor modalities, up to purely outdoor flight maneuvers in a challenging Mars analog environment to simulate scenarios which current and future Mars helicopters would need to perform. The presented work aims to provide data that reflects real-world scenarios and sensor effects. The extensive sensor suite includes various sensor categories, including multiple Inertial Measurement Units (IMUs) and cameras. Sensor data is made available as raw measurements and each data set provides highly accurate ground truth, including the outdoor experiments where a dual Real-Time Kinematic (RTK) Global Navigation Satellite System (GNSS) setup provides sub-degree and centimeter accuracy (1-sigma). The sensor suite also includes a dedicated high-rate IMU to capture all the vibration dynamics of the vehicle during flight to support research on novel machine learning-based sensor signal enhancement methods for improved localization. The data sets and post-processing tools are available at: https://sst.aau.at/cns/datasets

The Defense Ministry plans to deploy small attack drones in a bid to strengthen the defense of the nation's remote islands. The ministry will make preparations for the deployment, introducing U.S.-made and other drones in fiscal 2023 on a trial basis. It aims to deploy several hundred attack drones from fiscal 2025 at the earliest. This could be due to a conflict with your ad-blocking or security software. Please add japantimes.co.jp and piano.io to your list of allowed sites. If this does not resolve the issue or you are unable to add the domains to your allowlist, please see this support page.

We describe the orchestration of a decentralized swarm of rotary-wing UAV-relays, augmenting the coverage and service capabilities of a terrestrial base station. Our goal is to minimize the time-average service latencies involved in handling transmission requests from ground users under Poisson arrivals, subject to an average UAV power constraint. Equipped with rate adaptation to efficiently leverage air-to-ground channel stochastics, we first derive the optimal control policy for a single relay via a semi-Markov decision process formulation, with competitive swarm optimization for UAV trajectory design. Accordingly, we detail a multiscale decomposition of this construction: outer decisions on radial wait velocities and end positions optimize the expected long-term delay-power trade-off; consequently, inner decisions on angular wait velocities, service schedules, and UAV trajectories greedily minimize the instantaneous delay-power costs. Next, generalizing to UAV swarms via replication and consensus-driven command-and-control, this policy is embedded with spread maximization and conflict resolution heuristics. We demonstrate that our framework offers superior performance with respect to average service latencies and average per-UAV power consumption: 11x faster data payload delivery relative to static UAV-relay deployments and 2x faster than a deep-Q network solution; remarkably, one relay with our scheme outclasses three relays under a joint successive convex approximation policy by 62%.

Zurich - Founded in 2021, medtech aiEndoscopic combines artificial intelligence (AI) with robotic endoscopy. Its first development, intuBot, presents an all-in-one solution for airway management. It aims to make the life-saving process of endotracheal intubation, used in emergency medicine in particular, much easier and thus save lives. It is based on a collaborative project with ETH Zurich, University Hospital Zurich, and the University of Zurich. Additionally, the startup has been selected to form part of the Switzerland Innovation Park Zürich as well as to join the group of Swiss Venture Leaders Medtech 2022.

Gather AI, a startup using drones to inventory items in warehouses, today announced that it raised $10 million in a Series A round led by Tribeca Venture Partners with participation from Xplorer Capital, Dundee Venture Capital, Expa, Bling Capital, XRC Labs and 99 Tartans. The proceeds bring the company's total raised to $17 million, which CEO Sankalp Arora says is being put toward expanding Gather's deployment capacity and go-to-market plans as well as hiring new machine learning engineers. Arora co-founded Gather AI in 2019 with Daniel Maturana and Geetesh Dubey, graduate students at Carnegie Mellon's Robotics Institute. The trio had the idea to use drones to gather data -- specifically data in warehouses, such as the number of items on a shelf and the locations of particular pallets. Over the course of several years, they designed a prototype of an inventory monitoring system that used off-the-shelf autonomous drones, which became Gather's core product.