Breakthroughs, discoveries, and DIY tips sent every weekday. On July Fourth, amid a cacophony of fireworks and flame-throwing propane grills, a seemingly ordinary lightning strike hit somewhere in Grand Canyon National Park. The resulting spark ignited surrounding dry vegetation, and strong winds quickly spread the flames for miles. Over the course of several weeks, that initial spark has grown into a blaze engulfing more than 100,000 acres, officially classifying it as a "megafire" and the largest wildfire of 2025…so far. As of this writing, "The Dragon Bravo Fire" has already destroyed 70 buildings, including the historic Grand Canyon Lodge.

Ukrainian President Volodymyr Zelenskyy on Thursday urged his allies to bring about "regime change" in Russia, hours after a Russian drone and missile attack on Kyiv killed 16 people, including a 6-year-old boy. The overnight strikes reduced part of a nine-story apartment block in Kyiv's western suburbs to rubble and wounded at least 150 people in the capital, authorities said. The Russian army, meanwhile, claimed to have captured Chasiv Yar, a strategically important hillside town in eastern Ukraine where the two sides have been fiercely fighting for months.

In disaster response scenarios, deploying robotic teams effectively is crucial for improving situational awareness and enhancing search and rescue operations. The use of robots in search and rescue has been studied but the question of where to start robot deployments has not been addressed. This work addresses the problem of optimally selecting starting locations for robots with heterogeneous capabilities by formulating a joint optimization problem. To determine start locations, this work adds a constraint to the ergodic optimization framework whose minimum assigns robots to start locations. This becomes a little more challenging when the robots are heterogeneous (equipped with different sensing and motion modalities) because not all robots start at the same location, and a more complex adaptation of the aforementioned constraint is applied. Our method assumes access to potential starting locations, which can be obtained from expert knowledge or aerial imagery. We experimentally evaluate the efficacy of our joint optimization approach by comparing it to baseline methods that use fixed starting locations for all robots. Our experimental results show significant gains in coverage performance, with average improvements of 35.98% on synthetic data and 31.91% on real-world data for homogeneous and heterogeneous teams, in terms of the ergodic metric.

A House Democrat is moving to block the Trump administration from being able to use military-grade drones to surveil protests in the U.S. Rep. Jimmy Gomez, D-Calif., introduced the bill in response to the Department of Homeland Security (DHS) reportedly using MQ-9 Reaper drones to monitor the protests in Los Angeles earlier this year. "The U.S. government should never use military drones to spy on its own people. Not under anyone," Gomez told Fox News Digital in a statement. "This bill would stop Trump's abuse of power and get these combat drones out of our neighborhoods." An MQ-9 Reaper flies by on a training mission at Creech Air Force Base in Indian Springs, Nevada.

Russia launched a barrage of missile and drone attacks on Kyiv, killing at least six people – including a six-year-old boy and his mother – and injuring 52, according to Ukrainian officials. President Volodymyr Zelenskyy said on Thursday that Russian forces launched more than 300 drones and eight missiles, targeting residential buildings throughout the capital. "Today the world has once again seen Russia's response to our desire for peace with America and Europe. Therefore, peace without strength is impossible," Zelenskyy said on the Telegram app. Kyiv mayor Vitali Klitschko confirmed nine children were wounded in the attack, the highest number of child casualties in a single night in the city since Russia's full-scale invasion began nearly three and a half years ago.

A Russian drone and missile attack on Ukraine's capital has killed at least six people, including a six-year-old boy, according to Ukrainian President Volodymyr Zelenskyy and other officials. The overnight attack wounded at least 52 people and caused damage at 27 locations across four districts of Kyiv, city military administrator Tymur Tkachenko said on Thursday as casualty numbers are expected to rise. Rescue teams were at the scene to search for people trapped under the rubble. Russia's latest deadly attack on Ukraine came after United States President Donald Trump on Monday issued a 10- or 12-day ultimatum to Moscow to halt its invasion of Ukraine, now in its fourth year, or face sanctions. Zelenskyy said on Thursday that Russia had used more than 300 drones and eight missiles in the attack as he posted a video of burning ruins on social media.

Russian drone strikes on Ukraine's capital, Kyiv, on Wednesday night killed several people, including a six-year-old boy, as multiple locations across the city were hit including a hospital and a residential building.

A Russian drone attack in the Ukrainian capital Kyiv has killed at least four people, the Ground Forces of the Armed Forces of Ukraine said on Telegram. The debris from downed Russian drones fell near a garage cooperative, which led to the ignition of a gas pipe in a three-storey residential building. A Russian missile strike on a Ukrainian military training unit on Tuesday killed three servicemen and injured 18 more, Ukraine's Ground Forces also announced on Telegram. Russian forces shelled Ukrainian emergency service workers who had just put out a fire in the city of Orikhiv in southern Ukraine's Zaporizhia region, the State Emergency Service of Ukraine said in a post on Facebook. Ukraine's domestic security agency has detained an air force officer holding the rank of major on charges of having spied for Russia by leaking the location and suggesting strike tactics on prized, Western-donated F-16 and Mirage 2000 fighter jets.

The tiny "stealth" Carbon Voyager 1, fast-moving Black Tide I, and explosives-carrying Sea Shark 800 were the highlight of an expo for companies vying to help Taiwan build up a maritime drone force. Taipei believes drones could be pivotal in repelling China in the event its forces attempt to invade the self-ruled island, which Beijing has threatened to annex by force if necessary. Su'ao is just 60km (37 miles) from Fulong, one of the so-called "red beaches" identified by defence experts as potential landing sites for the People's Liberation Army (PLA) due to their unique topography. Whereas Russia sent tanks across land borders to launch its war on Ukraine in 2022, a Chinese invasion of Taiwan would involve Beijing sending vessels across the 180-km- (112-mile-)wide Taiwan Strait. While the Taiwan Strait's choppy waters and Taiwan's mountainous geography and shallow beaches pose formidable challenges to an amphibious invasion, technological advances and a decades-long modernisation campaign by the PLA have steadily chipped away at the island's natural defences.

A drone trajectory planner should be able to dynamically adjust the safety-efficiency trade-off according to varying mission requirements in unknown environments. Although traditional polynomial-based planners offer computational efficiency and smooth trajectory generation, they require expert knowledge to tune multiple parameters to adjust this trade-off. Moreover, even with careful tuning, the resulting adjustment may fail to achieve the desired trade-off. Similarly, although reinforcement learning-based planners are adaptable in unknown environments, they do not explicitly address the safety-efficiency trade-off. To overcome this limitation, we introduce a Decision Transformer-based trajectory planner that leverages a single parameter, Return-to-Go (RTG), as a \emph{temperature parameter} to dynamically adjust the safety-efficiency trade-off. In our framework, since RTG intuitively measures the safety and efficiency of a trajectory, RTG tuning does not require expert knowledge. We validate our approach using Gazebo simulations in both structured grid and unstructured random environments. The experimental results demonstrate that our planner can dynamically adjust the safety-efficiency trade-off by simply tuning the RTG parameter. Furthermore, our planner outperforms existing baseline methods across various RTG settings, generating safer trajectories when tuned for safety and more efficient trajectories when tuned for efficiency. Real-world experiments further confirm the reliability and practicality of our proposed planner.