Articles tagged with Lidar
Researchers propose integrated metasurfaces that can be combined with standard optical components like LEDs and LCDs for commercialization. Collaboration between industry and academia is crucial for developing innovative optical platforms.
Researchers at the University of Exeter have identified a Roman road network spanning Devon and Cornwall using LiDAR scans and geographical modelling. The network, which connected settlements with military forts, reveals that North Tawton was a strategically vital connection point.
A new approach boosts light absorption in thin silicon photodetectors with photon-trapping structures, increasing the absorption efficiency over a wide band in the NIR spectrum. The findings demonstrate a promising strategy to enhance the performance of Si-based photodetectors for emerging photonics applications.
Researchers have proposed an innovative solution to address limitations of lidar technology, enabling imaging in low SNR environments. The novel technique uses a high-scanning speed AOD and metasurface-enhanced scanning lidar, extending ambiguity range by up to 35 times.
A team of researchers from EPFL has found a way to harness the unique features of chaotic frequency combs to implement unambiguous and interference-immune massively parallel laser ranging. This innovative approach offers significant advantages over conventional methods, enabling hundreds of multicolor independent optical carriers.
A novel coupling mechanism involving leaky mode has been uncovered, enabling zero crosstalk between closely spaced waveguides. This discovery drastically increases the coupling length of transverse-magnetic (TM) mode, expanding the potential for dense photonic integration.
Researchers developed a compact and efficient single-photon Raman lidar system that can detect oil spills in the ocean. The system uses just 1μJ of pulse energy and can be operated up to 1km underwater, making it suitable for monitoring leaks in underwater oil pipelines.
Researchers at the University of Otago have discovered a new area of coastal uplift in Rarangi, Marlborough, using laser mapping and kelp genetics. The study provides new insights into Aotearoa's landscapes and recent earthquake impacts.
Researchers have developed a quantum lidar system that uses single-photon detection to acquire high-resolution 3D images underwater. The technology has the potential to inspect underwater installations, monitor submerged archaeology sites, and enhance security applications.
A new technique called image-free single-pixel object detection (SPOD) can detect the location, size, and category of multiple objects without acquiring images. SPOD uses a small optimized structured light pattern to quickly scan the scene and extract features, achieving an accuracy of over 80%.
A new phenotyping approach analyzes crop traits at the 3D level using a rail-based field phenotyping platform with LiDAR and an RGB camera. The method provides accurate quantification of crop traits such as plant height, leaf shape, and leaf color.
Scientists at EPFL and IBM have developed a new type of laser using lithium niobate, enabling precise distance measurements in LiDAR applications. The hybrid integrated tunable laser offers low frequency noise and fast wavelength tuning.
A new LiDAR system pinpoints pedestrian behavior to improve safety and efficiency at intersections. The system tracks pedestrians' true intent to cross, reducing conflicts between pedestrians and vehicles.
Researchers developed an algorithm that uses computer vision techniques to estimate tree diameter from a single image in realistic field conditions. The app sped up the process significantly, being about four and a half times faster than manual measurement techniques.
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.
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.
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 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.
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.
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 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.
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.
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.
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.