The US Army is looking to build an autonomous charging system that can support hundreds of drones. It has funded a four-year research project with the ultimate aim of kitting out ground-based vehicles with charging stations that swarms of drones can fly to by themselves. The University of Illinois Chicago landed an $8 million contract from the Combat Capabilities Development Command's Army Research Laboratory. Researchers will work on a system that will enable small drones to determine the location of the closest charging station, travel there and juice up before returning to their mission. The university is working on algorithms to help the drones determine the best route to a charging port.

Japan Post Co. unveiled Wednesday a self-driving mail delivery robot as demand grows for minimizing human contact amid the coronavirus pandemic. Using built-in cameras and sensors, the robot -- which is the size of a wheelchair -- operated on a sidewalk in Tokyo's Chiyoda Ward, dodging obstacles such as utility poles, and crossed an intersection with traffic lights. The robot is in the middle of a series of test runs that began on Sept. 18 and runs through late October. One of the tests involves the robot traveling 700 meters from a convenience store in a hospital to a local post office in about 25 minutes. The red DeliRo robot developed by ZMP Inc. is capable of carrying packages weighing up to 30 kilograms at a speed of 6 kilometers per hour, according to Japan Post, which aims to put the self-driving delivery robots into practical use in fiscal 2021.

Drone startup Skydio today announced the U.S. Federal Aviation Administration (FAA) has granted the North Carolina Department of Transportation (NCDOT) statewide approval to fly Skydio drones beyond visual line of sight to inspect bridges. Skydio, which describes the waiver as the first of its kind, says the NCDOT will be able to conduct maintenance activities without the use of visual observers like trained pilots or staff. A recent study by the American Association of State Highway and Transportation Officials found that taxpayer cost per bridge inspection can be reduced 75% by switching from traditional methods to drones. The Minnesota Department of Transportation found that using drones for bridge inspection offsets some or all of the costs, depending on the bridge configuration and location, with a trial of drone-assisted inspections saving an average of 40% over traditional methods and providing ostensibly superior data and reporting. Going forward, the NCDOT's inspectors can send Skydio 2 drones to inspect critical structures below bridges in North Carolina instead of conducting rappels or using "snooper trucks."

Powerful local processors can remove the need for a device to have a cloud connection. Along the coastline of Australia's New South Wales (NSW) state hovers a fleet of drones, helping to keep the waters safe. Earlier this year, the drones helped lifeguards at the state's Far North Coast rescue two teenagers who were struggling in heavy surf. The drones are powered by artificial-intelligence (AI) and machine-vision algorithms that constantly analyze their video feeds and highlight items that need attention: say, sharks, or stray swimmers. This is the same kind of technology that enables Google Photos to sort pictures, a home security camera to detect strangers, and a smart fridge to warn you when your perishables are close to their expiration dates.

Unmanned Aerial Vehicles (UAVs), or drones, have recently been used in several civil application domains from organ delivery to remote locations to wireless network coverage. These platforms, however, are naturally unstable systems for which many different control approaches have been proposed. Generally based on classic and modern control, these algorithms require knowledge of the robot's dynamics. However, recently, model-free reinforcement learning has been successfully used for controlling drones without any prior knowledge of the robot model. In this work, we present a framework to train the Soft Actor-Critic (SAC) algorithm to low-level control of a quadrotor in a go-to-target task. All experiments were conducted under simulation. With the experiments, we show that SAC can not only learn a robust policy, but it can also cope with unseen scenarios. Videos from the simulations are available in https://www.youtube.com/watch?v=9z8vGs0Ri5g and the code in https://github.com/larocs/SAC_uav.

This paper presents a novel algorithm named the motion-encoded particle swarm optimization (MPSO) for finding a moving target with unmanned aerial vehicles (UAVs). From the Bayesian theory, the search problem can be converted to the optimization of a cost function that represents the probability of detecting the target. Here, the proposed MPSO is developed to solve that problem by encoding the search trajectory as a series of UAV motion paths evolving over the generation of particles in a PSO algorithm. This motion-encoded approach allows for preserving important properties of the swarm including the cognitive and social coherence, and thus resulting in better solutions. Results from extensive simulations with existing methods show that the proposed MPSO improves the detection performance by 24\% and time performance by 4.71 times compared to the original PSO, and moreover, also outperforms other state-of-the-art metaheuristic optimization algorithms including the artificial bee colony (ABC), ant colony optimization (ACO), genetic algorithm (GA), differential evolution (DE), and tree-seed algorithm (TSA) in most search scenarios. Experiments have been conducted with real UAVs in searching for a dynamic target in different scenarios to demonstrate MPSO merits in a practical application.

Based on the hurricane struking Puerto Rico in 2017, we developed a transportable disaster response system "DroneGo" featuring a drone fleet capable of delivering medical package and videoing roads. Assuming equal weight for both mission, we take the capability of carrying out the former missions as a constraint and a starting point from which reconnaissance routes are built. The feasibility of fitting packages into cargo bay 1 or 2 is tested by genetic algorithm. In scenario where drones carry packages to and unloaded back, from specification of drones and loading weight can we derive the maximum reachable distance of each drone loaded. A k-means clustering algorithm is used for partitioning destinations and deriving centroids as locations of bases.

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LAS VEGAS – At 18 months old, Chris Rodriguez was diagnosed with heart failure and required a transplant. "My heart was pumping too much blood and my organs couldn't deal with it," said Rodriguez, now 14. "Most of my life, I've just been in and out of the hospital. More than 100,000 people are on the national transplant waiting list, and approximately 17 people die each day waiting to receive an organ transplant, according to the Health Resources and Services Administration. COVID-19 has complicated the situation even more, as travel restrictions and fewer commercial flights have made it difficult to transplant organs and highlighted the need for alternative travel methods to deliver vital organs. Nevada Donor Network partnered with MissionGo to test drones to deliver vital organs. "As a result of the COVID-19 pandemic, we have been subjected to fewer commercial flights to be able to transport organs for transplantation," Joe Ferreira, Nevada Donor Network CEO said. "We've had to look ...

Despite a recent COVID-19 outbreak in the NFL that resulted in cancelled games, some teams are planning to welcome back fans over the next few weeks. The Atlanta Falcons are one of those, and to reduce the risks, Atlanta's Mercedes-Benz Stadium (MBS) will be among the first sports venues to sanitize key areas using drones (via CNN). MBS will use Lucid Drone Technologies' D1 disinfecting drones to disinfect the seating bowl, handrails, and glass partitions at the stadium. "This stadium is incredibly large and as we begin to slowly welcome fans back, these drones allow us to maximize the time between games and private events to thoroughly sanitize," said building operations manager Jackie Poulakos. The use of drones reduces seating bowl cleaning times by 95 percent and is 14 times more efficient than regular backpack foggers, according to MBS.