Ukraine's human rights ombudsman has urged international organisations to respond to an allegation that several Ukrainian prisoners of war were executed in Russia's Kursk region. DeepState, a Ukrainian battlefield analysis site close to Ukraine's Defence Ministry, said that Russian troops killed nine Ukrainian "drone operators and contractors" on October 10 after they had surrendered. Dmytro Lubinets said on Sunday that the international community "must not turn a blind eye" to the alleged executions. The ombudsman wrote on Telegram that he had sent letters to the United Nations and the International Red Cross about the incident, referring to it as "another crime committed by the Russians". Ukrainian Prosecutor-General Andriy Kostin also said his office had opened a criminal investigation into the alleged execution and said killing prisoners of war was a "gross violation" of the Geneva Convention.

A mysterious fleet of drones entered restricted airspace and swarmed a U.S. military base along the Virginia coast for 17 days late last year, stumping the Pentagon, according to a new report. For several nights last December, U.S. military personnel reported witnessing a fleet of unknown unmanned aircraft breach restricted airspace over a stretch of land at Langley Air Force Base along Virginia's shore, the Wall Street Journal first reported. The drones would start to arrive about 45 minutes to an hour after sunset each night, one official reportedly told U.S. Air Force Gen. Mark Kelly, who joined several other officers responsible for the country's most advanced jet fighters, including F-22 Raptors, on a squadron rooftop. Kelly described the first drone he saw as roughly 20 feet long and flying at more than 100 miles an hour, at an altitude of roughly 3,000 to 4,000 feet. As many as a dozen or more drones followed, flying across Chesapeake Bay, and then traveling toward Norfolk, Virginia, and through a space overlooking the base for the Navy's SEAL Team Six and Naval Station Norfolk, the world's largest naval port, according to the Journal.

Motion planning is an essential process for the navigation of unmanned aerial vehicles (UAVs) where they need to adapt to obstacles and different structures of their operating environment to reach the goal. This paper presents an optimal motion planner for UAVs operating in unknown complex environments. The motion planner receives point cloud data from a local range sensor and then converts it into a voxel grid representing the surrounding environment. A local trajectory guiding the UAV to the goal is then generated based on the voxel grid. This trajectory is further optimized using model predictive control (MPC) to enhance the safety, speed, and smoothness of UAV operation. The optimization is carried out via the definition of several cost functions and constraints, taking into account the UAV's dynamics and requirements. A number of simulations and comparisons with a state-of-the-art method have been conducted in a complex environment with many obstacles to evaluate the performance of our method. The results show that our method provides not only shorter and smoother trajectories but also faster and more stable speed profiles. It is also energy efficient making it suitable for various UAV applications.

Abstract-- We present an integrated UAV-hexapod robotic system designed for GNSS-denied maritime operations, capable of autonomous deployment and retrieval of a hexapod robot via a winch mechanism installed on a UAV. This system is intended to address the challenges of localization, control, and mobility in dynamic maritime environments. Experimental results demonstrate the effectiveness of this system in real-world scenarios, validating its performance during field tests in both controlled and operational conditions in the MBZIRC 2023 Maritime Challenge. I. INTRODUCTION Unmanned Aerial Vehicles (UAVs) have become an essential component of modern robotics, widely used in various applications, including surveillance, inspection, search and Figure 1: UAV-Hexapod system executing its mission in a rescue, and transportation. Their ability to fly over challenging GNSS-denied maritime environment. Team KAIST won 2nd terrains and access remote areas has expanded the place in the MBZIRC 2023 Maritime Challenge.

Drone footage captured in St. Lucie County, Palm Beach Gardens, St. Petersburg, and Siesta Key shows damage to homes and structures after Hurricane Milton and multiple tornadoes tore across the state.

Mobile robots rely on maps to navigate through an environment. In the absence of any map, the robots must build the map online from partial observations as they move in the environment. Traditional methods build a map using only direct observations. In contrast, humans identify patterns in the observed environment and make informed guesses about what to expect ahead. Modeling these patterns explicitly is difficult due to the complexity of the environments. However, these complex models can be approximated well using learning-based methods in conjunction with large training data. By extracting patterns, robots can use direct observations and predictions of what lies ahead to better navigate an unknown environment. In this dissertation, we present several learning-based methods to equip mobile robots with prediction capabilities for efficient and safer operation. In the first part of the dissertation, we learn to predict using geometrical and structural patterns in the environment. Partially observed maps provide invaluable cues for accurately predicting the unobserved areas. We first demonstrate the capability of general learning-based approaches to model these patterns for a variety of overhead map modalities. Then we employ task-specific learning for faster navigation in indoor environments by predicting 2D occupancy in the nearby regions. This idea is further extended to 3D point cloud representation for object reconstruction. Predicting the shape of the full object from only partial views, our approach paves the way for efficient next-best-view planning. In the second part of the dissertation, we learn to predict using spatiotemporal patterns in the environment. We focus on dynamic tasks such as target tracking and coverage where we seek decentralized coordination between robots. We first show how graph neural networks can be used for more scalable and faster inference.

The same types of consumer-grade hobby drones heard buzzing overhead at the beach may play a key role in uncovering the Earth's remaining hidden species. For the first time, researchers recently used such a drone to discover and describe a new species of carnation hanging off of towering vertical cliffs in Hawaii. The revelation was made possible thanks to rapid advancements in drone sensor technology and a new, custom-designed claw-like plant extraction device. Details of the discovery were published this week in open access journal PhytoKeys. The newly described carnation, called Schiedea waiahuluensis, was spotted hanging off cliffs in the Waiahulu region of Hawaii's Kauaʻi island.

Locals and emergency responders are only just beginning to assess the total damage incurred from Hurricane Milton, but one early example of the historic storm's intensity is already on clear display. In the early hours of October 10th, extreme weather documentarian Brandon Clement uploaded nine minutes of ground and drone footage that showcased the destructive effects of 100 mph sustained winds on St. Petersburg's Tropicana Field, home to MLB's Tampa Bay Rays. As local news outlet WFLA explained on Thursday, the baseball team's home field was topped by fabric paneling that served as its roofing, an estimated two-thirds of which is now either shredded or gone completely. It's currently unclear if Tropicana Field suffered serious interior damage, but Clement's aerial images reveal substantial amounts of debris scattering the field, stands, and surrounding areas that includes what appears to be hundreds of cots. City officials previously intended to use the Rays' stadium as a hub for emergency worker coordinating efforts, but it's unclear how the facility's current state will affect response logistics in the coming days.

The Israeli military "repeatedly" fired at UNIFIL headquarters and positions in southern Lebanon, injuring two members of the peacekeeping force, the United Nations says, as Israel presses on with its assault on Hezbollah. UNIFIL – the UN Interim Force in Lebanon – said on Thursday that two of its peacekeepers were injured after an Israeli tank "fired its weapon" at a guard tower at the group's headquarters, located in the border area town of Naqoura. The attack on the tower had caused the two peacekeepers to fall. "The injuries are fortunately, this time, not serious, but they remain in hospital," said UNIFIL in a statement. The Israeli soldiers also fired on a UN position – named "1-31"- in the village of Labbouneh, "hitting the entrance to the bunker where peacekeepers were sheltering, and damaging vehicles and a communications system", it said. The peacekeeping force reported that it had observed an Israeli military drone flying inside the UN position up to the bunker entrance.

Russia's overnight attacks on Ukraine also left several people wounded in the southern city of Zaporizhzhia. Meanwhile, Ukrainian drones targeted a military airfield in the Maikop region of southern Russia. Local officials evacuated 40 people from a nearby village. Russia's missile strike on the Odesa region hit a Panamanian-registered ship on Wednesday night, Oleh Kiper said - two days after a Palau-flagged ship was attacked, leaving one dead on board. Another ship, which was said to be carrying 6,000 tonnes of corn, was attacked on Sunday.