'Nature seems to have already solved the problem.' Breakthroughs, discoveries, and DIY tips sent six days a week. To help figure out what makes stingrays such unique and unusual swimmers, a team of mechanical engineers at the University of California, Riverside (UCR) created a wavy robotic fin. After submerging the robot in underwater tunnels designed to mimic swimming near the sea floor, their tests indicate that different types of ray species may have evolved alternative swimming techniques that best suit their setting. Specifically, the findings suggest that some ray species swimming near the seafloor adjust the way their fins move and tilt to counter a downward force that would otherwise pull them toward the ground. It turns out that stingrays gracefully gliding along waves near seabeds aren't doing it to look cool.

In order to find the country location for each video in previous Y ouTube-based datasets (e.g., Kinetics, HACS, etc.), we used the public Y ouTube API. 'The geolocation information associated with the video. In our measure, roughly 8% of the videos had such geolocation. We then used reverse-geocode library https://pypi.org/project/reverse-geocode/

Amphibians adapt their morphologies and motions to accommodate movement in both terrestrial and aquatic environments. Inspired by these biological features, we present PuffyBot, an untethered shape morphing robot capable of changing its body morphology to navigate multiple environments. Our robot design leverages a scissor-lift mechanism driven by a linear actuator as its primary structure to achieve shape morphing. The transformation enables a volume change from 255.00 cm3 to 423.75 cm3, modulating the buoyant force to counteract a downward force of 3.237 N due to 330 g mass of the robot. A bell-crank linkage is integrated with the scissor-lift mechanism, which adjusts the servo-actuated limbs by 90 degrees, allowing a seamless transition between crawling and swimming modes. The robot is fully waterproof, using thermoplastic polyurethane (TPU) fabric to ensure functionality in aquatic environments. The robot can operate untethered for two hours with an onboard battery of 1000 mA h. Our experimental results demonstrate multi-environment locomotion, including crawling on the land, crawling on the underwater floor, swimming on the water surface, and bimodal buoyancy adjustment to submerge underwater or resurface. These findings show the potential of shape morphing to create versatile and energy efficient robotic platforms suitable for diverse environments.

Abstract-- In this paper we present an underactuated biomimetic underwater robot that is suitable for ecosystem monitoring in both marine and freshwater environments. We present an updated mechanical design for a fish-like robot and propose minimal actuation behaviors learned using reinforcement learning techniques. We present our preliminary mechanical design of the tail oscillation mechanism and illustrate the swimming behaviors on FishGym simulator, where the reinforcement learning techniques will be tested on. I. INTRODUCTION Recent years have seen growing interest in underwater exploration for ecosystem monitoring, marine education, navigation and rescue. Bio-inspired soft robots, particularly fish-like ones, are well suited for observing marine ecosystems that are fragile and undisturbed.

Traditional human activity recognition uses either direct image analysis or data from wearable inertial measurement units (IMUs), but can be ineffective in challenging underwater environments. We introduce a novel hybrid approach that bridges this gap to monitor scuba diver safety. Our method leverages computer vision to generate high-fidelity motion data, effectively creating a ``pseudo-IMU'' from a stream of 3D human joint keypoints. This technique circumvents the critical problem of wireless signal attenuation in water, which plagues conventional diver-worn sensors communicating with an Autonomous Underwater Vehicle (AUV). We apply this system to the vital task of identifying anomalous scuba diver behavior that signals the onset of a medical emergency such as cardiac arrest -- a leading cause of scuba diving fatalities. By integrating our classifier onboard an AUV and conducting experiments with simulated distress scenarios, we demonstrate the utility and effectiveness of our method for advancing robotic monitoring and diver safety.

A great white shark was spotted this week swimming in the area of Scarborough, Maine. A drone video captured a great white shark lurking in the waters of a vacation spot in the Northeast. Police in Scarborough, Maine, which is located just south of Portland, confirmed this week that the shark was spotted off the state's coastline. "On Monday, August 11, 2025, Scarborough's Marine Resource Officer received a report of what appeared to be a large shark near Richmond Island and Scarborough Beach," the town wrote on its Facebook page. "Follow-up observations were conducted, and on Tuesday, August 12, 2025, the Marine Resource Officer obtained drone video footage showing a possible great white shark, estimated to be 10–12 feet in length, off the southern end of Richmond Island in the vicinity of Higgins Beach and Scarborough Beach," it added.

We present an evolved steerable version of the single-tail Fish-&-Ribbon-Inspired Small Swimming Harmonic roBot (FRISSHBot), a 59-mg biologically inspired swimmer, which is driven by a new shape-memory alloy (SMA)-based bimorph actuator. The new FRISSHBot is controllable in the two-dimensional (2D) space, which enabled the first demonstration of feedback-controlled trajectory tracking of a single-tail aquatic robot with onboard actuation at the subgram scale. These new capabilities are the result of a physics-informed design with an enlarged head and shortened tail relative to those of the original platform. Enhanced by its design, this new platform achieves forward swimming speeds of up to 13.6 mm/s (0.38 Bl/s), which is over four times that of the original platform. Furthermore, when following 2D references in closed loop, the tested FRISSHBot prototype attains forward swimming speeds of up to 9.1 mm/s, root-mean-square (RMS) tracking errors as low as 2.6 mm, turning rates of up to 13.1 °/s, and turning radii as small as 10 mm.

Ukraine's military has said it struck an oil refinery in Russia's Saratov region in an overnight drone attack, causing explosions and destruction, according to an army statement, as daily aerial exchanges intensify with diplomatic momentum to end the war in play. Saratov's governor said on Sunday that one person was killed and several residential apartments and an industrial facility were damaged, but did not mention the oil refinery being struck. "[Ukrainian] drones are targeting … deeper into Russian territory [than] in the past, where previous attacks have been focused on the line of contact in the south and the western parts of Russia," said Al Jazeera's Osama Bin Javaid, reporting from Moscow. It is still unclear whether Ukraine's claims that it hit a refinery are true, he added. Ukraine's military also said on Sunday that it had taken back a village in the Sumy region from the Russian army, which has made significant recent gains there.

Fish have endured millions of years of evolution, and their distinct rigid-flexible body structures offer inspiration for overcoming challenges in underwater robotics, such as limited mobility, high energy consumption, and adaptability. This paper introduces SpineWave, a biomimetic robotic fish featuring a fish-spine-like rigid-flexible transition structure. The structure integrates expandable fishbone-like ribs and adjustable magnets, mimicking the stretch and recoil of fish muscles to balance rigidity and flexibility. In addition, we employed an evolutionary algorithm to optimize the hydrodynamics of the robot, achieving significant improvements in swimming performance. Real-world tests demonstrated robustness and potential for environmental monitoring, underwater exploration, and industrial inspection. These tests established SpineWave as a transformative platform for aquatic robotics.