Rep. Chris Smith, R-N.J., opens up about the aerial systems spotted in the Garden State on'The Story.' A Chinese citizen living in Los Angeles allegedly flew a drone and took aerial images of Vandenberg Space Force Base last month, federal prosecutors said Monday. Yinpiao Zhou, 39, was arrested this week at the San Francisco International Airport prior to boarding a China-bound flight, the Justice Department said. He is charged with failure to register an aircraft not providing transportation and violation of national defense airspace. On Nov. 30, drone detections systems at the military installation in Santa Barbara County detected a drone flying over the base, prosecutors said.

Autonomous air taxis are poised to revolutionize urban mass transportation, however, ensuring their safety and reliability remains an open challenge. Validating autonomy solutions on air taxis in the real world presents complexities, risks, and costs that further convolute this challenge. Verification and Validation (V&V) frameworks play a crucial role in the design and development of highly reliable systems by formally verifying safety properties and validating algorithm behavior across diverse operational scenarios. Advancements in high-fidelity simulators have significantly enhanced their capability to emulate real-world conditions, encouraging their use for validating autonomous air taxi solutions, especially during early development stages. This evolution underscores the growing importance of simulation environments, not only as complementary tools to real-world testing but as essential platforms for evaluating algorithms in a controlled, reproducible, and scalable manner. This work presents a V&V framework for a vision-based landing system for air taxis with vertical take-off and landing (VTOL) capabilities. Specifically, we use Verse, a tool for formal verification, to model and verify the safety of the system by obtaining and analyzing the reachable sets. To conduct this analysis, we utilize a photorealistic simulation environment. The simulation environment, built on Unreal Engine, provides realistic terrain, weather, and sensor characteristics to emulate real-world conditions with high fidelity. To validate the safety analysis results, we conduct extensive scenario-based testing to assess the reachability set and robustness of the landing algorithm in various conditions. This approach showcases the representativeness of high-fidelity simulators, offering an effective means to analyze and refine algorithms before real-world deployment.

Navigating unmanned aerial vehicles in environments where GPS signals are unavailable poses a compelling and intricate challenge. This challenge is further heightened when dealing with Nano Aerial Vehicles (NAVs) due to their compact size, payload restrictions, and computational capabilities. This paper proposes an approach for localization using off-board computing, an off-board monocular camera, and modified open-source algorithms. The proposed method uses three parallel proportional-integral-derivative controllers on the off-board computer to provide velocity corrections via wireless communication, stabilizing the NAV in a custom-controlled environment. Featuring a 3.1cm localization error and a modest setup cost of 50 USD, this approach proves optimal for environments where cost considerations are paramount. It is especially well-suited for applications like teaching drone control in academic institutions, where the specified error margin is deemed acceptable. Various applications are designed to validate the proposed technique, such as landing the NAV on a moving ground vehicle, path planning in a 3D space, and localizing multi-NAVs. The created package is openly available at https://github.com/simmubhangu/eyantra_drone to foster research in this field.

Catalyzed by advancements in hardware and software, drone performances are increasingly making their mark in the entertainment industry. However, designing smooth and safe choreographies for drone swarms is complex and often requires expert domain knowledge. In this work, we introduce SwarmGPT-Primitive, a language-based choreographer that integrates the reasoning capabilities of large language models (LLMs) with safe motion planning to facilitate deployable drone swarm choreographies. The LLM composes choreographies for a given piece of music by utilizing a library of motion primitives; the language-based choreographer is augmented with an optimization-based safety filter, which certifies the choreography for real-world deployment by making minimal adjustments when feasibility and safety constraints are violated. The overall SwarmGPT-Primitive framework decouples choreographic design from safe motion planning, which allows non-expert users to re-prompt and refine compositions without concerns about compliance with constraints such as avoiding collisions or downwash effects or satisfying actuation limits. We demonstrate our approach through simulations and experiments with swarms of up to 20 drones performing choreographies designed based on various songs, highlighting the system's ability to generate effective and synchronized drone choreographies for real-world deployment.

Fox News Flash top sports headlines are here. Check out what's clicking on Foxnews.com. New York Jets quarterback Aaron Rodgers lives in New Jersey and has noticed the drones recently flying throughout the state. "Do you know what's been going on in Jersey lately? There's been some crazy things going on. There is some drones in the sky," Rodgers said during a recent appearance on "The Pat McAfee Show."

Fox News contributor Brett Velicovich discusses House Subcommittee on Aerial Systems' role in investigating multiple sightings in the Garden State on'America Reports.' A top FBI leader revealed the agency knows concerningly little about the mysterious drones that have been seen hovering over New Jersey. Asked if Americans are "at risk," FBI Assistant Director of the Critical Incident Response Group Robert Wheeler told Congress: "There is nothing that is known that would lead me to say that, but we just don't know. Dozens of drones have been spotted flying near sensitive sites like a military research facility in recent weeks. The FBI has been investigating the incidents and has called on the public for additional information. According to Gov. Phil Murphy, there were 49 reports of drones on Sunday alone, mostly in Hunterdon County. The FBI assistant director's comments came during a joint hearing of two Homeland Security subcommittees on unmanned aerial systems. "We do not attribute that to an individual or a group yet.

Ken Gray, a former FBI agent and military analyst, told Fox News Digital he does not believe the New Jersey drone sightings are hobbyists, though it's unclear at this stage if they are a threat or not. New Jersey authorities have insisted that sightings of SUV-size drones for the past several weeks do not present a threat to public safety, but military analysts say the lack of clear answers from the government points to a larger problem. These large drones have been spotted over the skies of the Garden State with smaller, more rapidly maneuverable drones, resembling what's referred to as "drone motherships" that have been deployed in Ukraine, Russia and China, Fox News contributor Brett Velicovich said. The motherships launch smaller drones, which do not have the necessary range-antennas to carry them a further distance. That suggests, according to Velicovich, that a foreign adversary could be at play in New Jersey.

I was here to examine the pitch being made by Anduril, other companies in defense tech, and growing numbers of people within the Pentagon itself: A future "great power" conflict--military jargon for a global war involving competition between multiple countries--will not be won by the entity with the most advanced drones or firepower, or even the cheapest firepower. It will be won by whoever can sort through and share information the fastest. And that will have to be done "at the edge" where threats arise, not necessarily at a command post in Washington. "You're going to need to really empower lower levels to make decisions, to understand what's going on, and to fight," Anduril CEO Brian Schimpf says. "That is a different paradigm than today." To show how the new tech will fix that, Anduril walked me through an exercise demonstrating how its system would take down an incoming drone threatening a base of the US military or its allies (the scenario at the center of Anduril's new partnership with OpenAI).

'Fox & Friends Weekend' co-host Rachel Campos-Duffy opens up about seeing drones outside her home. U.S. lawmakers from New Jersey joined in many residents' frustrations over dozens of reports of drones being flown near sensitive sites like a military research facility in recent weeks, and they are now calling on federal agencies to immediately help investigate and address the escalating issue. Rep. Chris Smith, R-N.J., joined law enforcement leaders in his district on Monday on Long Beach Island, having been one of the key figures leading efforts to investigate the source and possible risks associated with the drone activity. "I have been speaking with Ocean County Sheriff Mike Mastronardy, Monmouth County Sheriff Shaun Golden, and national security officials located in the area to discuss the widespread reports of unidentified drone activity across my central New Jersey congressional district and across our state," Smith said in a statement. "Understandably, New Jersey residents are very alarmed at this significant and reoccurring phenomenon – and the tepid response from our state and federal agencies so far is totally unacceptable. As we saw with the Chinese spy balloon last year, our fiercest adversaries will stop at nothing to surveil our homeland and threaten our national security."

This paper proposes a novel trajectory generation method based on Model Predictive Control (MPC) for agile landing of an Unmanned Aerial Vehicle (UAV) onto an Unmanned Surface Vehicle (USV)'s deck in harsh conditions. The trajectory generation exploits the state predictions of the USV to create periodically updated trajectories for a multirotor UAV to precisely land on the deck of a moving USV even in cases where the deck's inclination is continuously changing. We use an MPC-based scheme to create trajectories that consider both the UAV dynamics and the predicted states of the USV up to the first derivative of position and orientation. Compared to existing approaches, our method dynamically modifies the penalization matrices to precisely follow the corresponding states with respect to the flight phase. Especially during the landing maneuver, the UAV synchronizes attitude with the USV's, allowing for fast landing on a tilted deck. Simulations show the method's reliability in various sea conditions up to Rough sea (wave height 4 m), outperforming state-of-the-art methods in landing speed and accuracy, with twice the precision on average. Finally, real-world experiments validate the simulation results, demonstrating robust landings on a moving USV, while all computations are performed in real-time onboard the UAV.