Articles tagged with Lidar
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Pathak and Simon are developing a cutting-edge unmanned aerial vehicle (UAV) and unmanned ground vehicle mmWave wireless networking platform at George Mason University. The platform will enable high-speed wireless connectivity and robust sensing for drones and ground vehicles, with potential applications in civilian and military domains.
A new technique maps the effects of fire-induced permafrost thaw in Alaska, revealing widespread topographic change and vegetation shifts. The study used a machine learning-based approach to quantify thaw settlement across 3 million acres of land, with results showing a significant loss of evergreen forest and shrubland encroachment.
Researchers developed a new non-mechanical 3D lidar system that combines scanning and flash illumination using a chip-based light source, enabling safe navigation in dynamic environments. The system can measure the distance of poorly reflective objects and track their motion, making autonomous driving safer.
Researchers from Utah State University have developed a new LiDAR system that improves the response time of commercial vehicles and detects movement without flaws. The technology can differentiate between stagnant and moving objects, see in the dark, and recognize potential collisions in real-time.
A new optical coating system combines antifogging and antireflective properties, enhancing the performance of lidar systems and cameras. The technology, developed by Fraunhofer Institute for Applied Optics and Precision Engineering, has been tested in laboratory tests and has shown promising results.
The three-year effort aims to establish a widely accepted protocol for comparing lidar performance. The first year's tests evaluated range, accuracy, and precision of eight automotive-grade lidars using a survey-grade reference. Results showed the distribution of measured values was not Gaussian, with significant errors in some cases.
Researchers at Columbia Engineering's Lipson Nanophotonics Group create tunable and narrow-linewidth chip-scale lasers emitting light of different colors, including green, blue, and violet. These inexpensive lasers have the smallest footprint and shortest wavelength of any tunable and narrow-linewidth integrated laser emitting visible ...
Researchers developed a one-dimensional suspended high-contrast grating structure to enable directional lasing with high energy efficiency. The device can adjust the emission angle over a wide range, from -40° to +40°, making it suitable for solid-state LiDAR applications.
A new study uses drone-mounted technology to deter bats from flying into wind turbines, reducing fatalities by 40% and allowing turbines to operate efficiently. The device transmits ultrasonic signals and lights to warn bats of danger, leading them to fly over the turbine and out of harm's way.
Researchers at Incheon National University have developed an IoT-enabled, real-time object detection system for autonomous vehicles. The YOLOv3-based model achieved high accuracy (>96%) in detecting 2D and 3D objects, outperforming other state-of-the-art detection models.
Researchers developed a new lidar technique using 3D flash lidar combined with super-resolution algorithm for hazard avoidance during landing. The technique improved the precision and safety of robotic vehicles on Mars, enabling them to navigate through challenging environments.
A new study developed a traveling-wave amplifier based on a photonic integrated circuit operating in the continuous regime, providing 7 dB net gain on-chip and 2 dB net gain fiber-to-fiber. This achievement enables unlimited application areas for LiDAR and other optical sensing applications.
A new research project at Aarhus University aims to develop intelligent drones that can detect ice on turbine blades, optimizing energy production and expanding market opportunities. The project has the potential to reduce energy losses by up to 80% and enable wind farms to operate in colder climates.
Researchers from the Bajo Laberinto Archaeological Project have used lidar technology to uncover a vast, complex urban sprawl beneath the Calakmul forest canopy. The study reveals dense apartment-style residential compounds, numerous temples and shrines, and extensive water management features.
A team of researchers from Pohang University of Science & Technology (POSTECH) has created a fixed LiDAR sensor that can see objects in all directions. The new sensor uses a metasurface to expand its viewing angle, allowing for 360° recognition and three-dimensional imaging.
A new type of integrated semiconductor laser has been developed using the Pockels effect, integrating a lithium-niobate-on-insulator platform. This technology enables fast reconfigurability and narrow spectral window, paving the way for applications in LiDAR remote sensing, microwave photonics, atomic physics, and AR/VR.
Researchers have developed a chemically sensitive lidar method that can map and identify the composition of environments, augmenting human interactions and industrial processes. The new technique resolves chemical information by detecting sub-nanometer surface deformations due to photothermal absorption.
Researchers have developed a novel computational imaging framework, Compact Light-field Photography (CLIP), allowing the camera system to acquire wide and deep panoramic views. The technology enables the detection of hidden objects around occlusions and has potential applications in autonomous vehicles and medical imaging.
Researchers have developed a new chip-based beam steering device that eliminates aliasing errors, enabling high-quality beam steering over large fields of view. The device, published in Optica, has the potential to revolutionize lidar applications in autonomous driving, virtual reality, and biomedical sensing.
The researchers achieved ultranarrow linewidths and wavelength tunability in the lithium niobate microlaser, enabling applications like lidar and metrology. The single-mode lasing is realized through simultaneous excitation of high-Q polygon modes at both pump and laser wavelengths.
Researchers developed a lidar-based system for smart cars to recognize objects more accurately than cameras. The system uses a grid map to divide the field of view into regions containing individual objects.
Researchers at EPFL have developed a photonic integrated circuit based erbium-doped amplifier that generates record output power and provides high gain, matching commercial EDFAs. This breakthrough enables new applications in optical communications, LiDAR, quantum sensing, and memories.
Archaeologists have discovered two remarkably large sites of 147 hectares and 315 hectares in a dense four-tiered settlement system using LIDAR technology. The largest site is as large as Bonn was in the 17th century, with modifications indicating a reasonable increase in population.
Researchers uncovered intricate settlements in Bolivia's Llanos de Mojos savannah-forest, featuring elaborate structures and a vast network of reservoirs. The cities were built alongside nature, employing successful sustainable subsistence strategies that promoted conservationism and maintained rich biodiversity.
Researchers used an ant-tracking method to estimate snow depth and found that it was approximately half the average distance a photon traveled inside the snow. This technique can help predict changes in sea ice thickness and glaciers, crucial for water resource management and climate modeling.
Developers are integrating optical coherence tomography (OCT) machines into sensor packages to create fast and accurate LiDAR systems. These advancements enable robots and cars to see the world in a more natural and safe manner, improving interaction with humans.
A team of researchers has developed a MEMS scanning lidar that can detect objects reliably even in shaky environments. The long-range MEMS lidar prototype uses a digital controller to suppress errors caused by vibrations, allowing for stable 3D imaging and object detection.
Researchers at Stanford University have developed a new approach to enable standard image sensors to capture light in three dimensions. The system uses acoustic resonance and piezoelectric properties of lithium niobate to modulate light, allowing for high-performance lidar capabilities in compact devices.
A machine learning algorithm uses data from two Earth observation satellites to determine the depth of optically shallow waters, improving navigation and coastal management. The study focused on tropical regions but aims to generate global high-resolution bathymetric maps for near-shore shallow regions.
Researchers at Duke University have demonstrated a new attack strategy that can deceive industry-standard autonomous vehicle sensors into believing nearby objects are closer or further than they appear. This vulnerability highlights the need for additional redundancy and data sharing between vehicles to protect against such attacks.
A new type of high-resolution LiDAR chip has been developed by the University of California, Berkeley, which could lead to a new generation of powerful, low-cost 3D sensors. The chip uses a focal plane switch array (FPSA) and achieves a resolution of 16,384 pixels.
Researchers at INRS developed a method to amplify weak optical signals while reducing noise content using the Talbot self-imaging effect. This technique has potential applications in various fields like telecommunications, bioimaging, and remote sensing.
Researchers from SUTD and A*STAR IMRE demonstrate the use of chalcogenide nanostructures to reversibly tune Mie resonances in the visible spectrum, paving the way for high resolution colour displays. The technology relies on phase change materials, including antimony trisulphide nanoparticles.
A new COVID-19 mobile robot detects social distancing breaches in crowds and encourages people to move apart using a novel system that employs Deep Reinforcement Learning and Frozone algorithm. The robot also incorporates a thermal camera for contact-tracing efforts, ensuring privacy protection and de-identification.
Research reveals Arctic rivers are discharging much more water than previously thought, with acceleration up to three times higher than estimated. The RADR project assimilates satellite information into hydrologic models for the entire pan-Arctic region.
Researchers at Nicolaus Copernicus University developed an algorithm to help robots avoid dead ends by predicting obstacles and using augmented reality. This innovation significantly improves the efficiency of mobile robots.
Ancestral puebloans in Chaco Canyon thrived for over a millennium through indigenous agriculture and water irrigation, but their activities led to environmental degradation. The researchers found significant changes in the local woodlands beginning around 600 B.C., contributing to severe erosion and cropland deterioration.
A UArizona-led team has discovered nearly 500 ancient ceremonial complexes in southern Mexico, similar to the largest Maya monument Aguada Fénix. The findings suggest that the Olmec civilization played a significant role in shaping the development of the Maya civilization.
A new methodology creates a watershed-scale flood model based on LiDAR data, providing precise elevation readings and riverbed depth information. The system can predict flood conditions and provide warnings to area residents, making it applicable to large rivers and smaller streams.
A recent discovery at Tikal reveals a previously unknown neighborhood designed to replicate Teotihuacan's citadel, sparking new insights into the interaction between the two civilizations. Excavations found evidence of occupation and surveillance, as well as artifacts linking Tikal to Teotihuacan's imperial power.
SUTD researchers develop sensor that assigns dirt score to areas based on visual and tactile analysis, allowing for more efficient exploration of complex spaces. The sensor is integrated with a smart algorithm that directs the robot to focus on areas with high dirt probability.
A lidar mapping study of ancient Teotihuacan shows that the city's engineers reshaped the landscape for construction, rerouted rivers to align with astronomical significance, and identified hundreds of previously unknown architectural features. The study confirms how these modifications continue to influence modern activities in the area.
Researchers developed a precise stopwatch to count single photons, enhancing imaging technologies like forest mapping and disease diagnosis. The new time lens technology improves photon timing resolution by orders of magnitude.
A team of researchers used remote sensing data and deep machine learning to identify hundreds of new shell ring sites in the southeastern US. The study provides a better understanding of how people lived in the area and offers a way to locate undiscovered shell rings.
Researchers applied supervised machine learning to lidar data from fishery surveys, automating the identification process in regions with a strong possibility of harboring fish. The technique decreased manual inspection in datasets from Yellowstone Lake and Gulf of Mexico studies by 61.14% and 26.8%, respectively.
Researchers found that mobile lidar scanning consistently provided accurate structural metrics and estimates of canopy cover and landscape metrics in various forest types and configurations. The technology has the potential to monitor a variety of forest attributes at a lower cost than other platforms.
A large measurement campaign has started in the Atlantic, using a TROPOS lidar on Cabo Verde to study atmospheric conditions and support the ESA wind satellite Aeolus. The campaign aims to improve weather forecasts and understand cloud and aerosol behavior in the tropics.
Twice a day, a faint layer of metals sinks down through the atmosphere at 90 miles high above Boulder, Colorado. The discovery provides a window into the high-altitude region where interactions between the sun, earth, and magnetic field can create conditions for surface life to thrive.
Researchers at Pohang University of Science & Technology (POSTECH) have developed a revolutionary LiDAR device the size of a finger using nanophotonics-based technology. The device can be used in autonomous vehicles, intelligent robots, drones, and augmented reality platforms.
A new study using airborne lidar sensing and machine-learning algorithms estimates that the Greater Angkor region was home to 700,000-900,000 people. The findings provide valuable insights into the region's population dynamics and its relevance to understanding urbanization in the face of climate change.
Researchers developed a 3D holographic head-up display using LiDAR data to create ultra-high-definition holographic representations of road objects, alerting drivers to potential hazards without distraction. The technology has shown promising results in early tests, suggesting it could be a valuable addition to existing safety measures.
A study using airborne laser scanning found that water stress, soil fertility, and anthropic forest degradation contribute to tree mortality in the Amazon. The researchers mapped gaps in the forest using LiDAR data, which showed a significant correlation with field mortality patterns.
Researchers developed a new noise-suppression technique that reduces noise photon counts by at least 50 times, enabling accurate 3D imaging up to 201.5 km with single-photon sensitivity. The technique is achieved through optimized transceiver optics and coating the telescope for high transmission.
Researchers from WMG, University of Warwick found that LiDAR sensors' effectiveness decreases in heavy rain, hindering object detection. The study simulated real-world roads and weather using the WMG 3xD simulator to test LiDAR sensor performance.
The US Corn Belt has lost around 35% of its organic-rich A-horizon soil through agricultural erosion, leading to a 6% decline in crop yields and $2.8 billion annual economic losses.
Researchers have developed a compact and high-performance 3D LiDAR imaging system using a silicon photonic component and CMOS electronic circuit in a single microchip. The prototype achieves accurate imaging and mapping, essential for autonomous cars, robots, drones, and healthcare applications.
Boulat Bash demonstrates how quantum methods can substantially increase reliable information sending over covert channels. By applying quantum resources to sensing, he identifies the 'sweet spot' where high noise and low power levels are beneficial for covert operations.
A Rochester Institute of Technology imaging scientist has received $194,000 in NGA grants and $197,000 from NASA to develop a new waveform LiDAR method that can create clearer 3D sub-canopy maps of forests. This technology will aid in identifying potential threats and understanding forest physiology.
A team of researchers demonstrated that popular robotic household vacuum cleaners can be remotely hacked to record speech and music. They used signal processing and deep learning techniques to recover sound waves from the laser-based navigation system, revealing potential security risks and privacy breaches.
A new radar system developed by UC San Diego engineers can accurately predict object shapes and sizes in various weather conditions. The two-sensor setup improves imaging quality compared to traditional single-radar systems.