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Recently, various calibration techniques proposed for extrinsic calibration for Autonomous Vehicles (AVs) mostly rely on the camera 2D images and depth map to calibrate the 3D LiDAR points. While most methods work with the whole frame, some methods use the objects in the frame to perform the calibration.

Light detection ranging (LiDAR) is commonly used to make high-resolution maps by using ultraviolet, visible, or near-infrared light to image objects. ...LiDAR-like systems combine laser-focused imaging with the ability to calculate distances by measuring the time for a signal to return using various electronic sensors. LiDAR data capturing has been conducted and verified from many types of equipment manufacturers, however, little research has compared the FARO Terrestrial Laser Scanner and the LiDAR sensor of an iPad Pro. ...LiDAR data capturing has been conducted and verified from many types of equipment manufacturers, however, little research has compared the FARO Terrestrial Laser Scanner and the LiDAR sensor of an iPad Pro. This study compares these two types of equipment addressing ease-of-use, effectiveness, and cost; where the Terrestrial Laser Scanner will be the control for this study.

The use of very short wavelength radar sensors for closed loop adaptive cruise control (ACC) and obstacle detection has been demonstrated as part of various international research and technology demonstration programs (e.g. PROMETHEUS in Europe). The first radar systems for distance measurement and target tracking are now under development, with vehicle trials already under way in several countries. This paper describes a 77 GHz radar sensor which will begin production next year (1999) as a headway sensor, initially for use in cruise control systems. The challenges facing the sensor manufacturer include the development of robust product designs and process technologies suited to the high volume and reliability demands of the automotive market, whilst achieving this at a sustainable production cost. The key design features of such a product are described, together with the major factors influencing cost and performance.

Abstract This article presents a novel approach to optimize the placement of light detection and ranging (LiDAR) sensors in autonomous driving vehicles using machine learning. As autonomous driving technology advances, LiDAR sensors play a crucial role in providing accurate collision data for environmental perception. ...As autonomous driving technology advances, LiDAR sensors play a crucial role in providing accurate collision data for environmental perception.

As for LiDAR SLAM system, it faces great challenges in scenarios where there are repetitive and sparse features. ...This paper proposes a construction method of LiDAR anchor constraints to improve the robustness of the SLAM system in the above challenging environment.

This challenge is addressed in this work for lidar sensors. The lidar equation was previously employed in this context to derive estimates of a lidar’s maximum range in different weather conditions. ...In this work, we present a stochastic simulation framework based on a probabilistic extension of the lidar equation, to quantify the effect of adverse rainfall conditions on a lidar’s raw detection performance. ...Combining the effect of other noise sources with the presented framework in a ray tracer is an opportunity for realistic physical lidar simulations and would allow to virtually estimate the performance of a lidar’s object detection and tracking performance.

The suggested method doesn’t need expensive additional sensors such as optical or lidar sensor, also it shows better performance in real car environment compared to other algorithms based on vehicle dynamics.

Firstly, based on the principle that parking spaces should be parallel or vertical to a corresponding path, a topological parking lot map is designed by using the point cloud data collected by LiDAR sensor. This map is consist of road node coordinates, adjacent matrix and parking space information.

Camera and a one-beam type Lidar are implemented together with Raspberry Pi. OpenCV free open source software is also used for developing lane detection and object recognition.

This paper discusses, how the decomposition approach from ISO 26262 can be applied for autonomous driving (AD) systems considering processing chain from sensors such as camera, radar, LIDAR, etc. to perception algorithms and decision algorithms which are executed in high performance chips.

Small Form Factor Embedded Systems New Technologies Drive Diverse Solutions Making Laser Weapons a Reality Modelling and Simulation Tools for Systems Integration on Aircraft Rotorcraft Anti-Icing Systems Redundant Transmitting System in Aircraft (RTSA) Cassini Stays in Touch with NASA's Radio Science Subsystem Laser Integration on Silicon Photonic Circuits Through Transfer Printing New fabrication approach allows the massively parallel transfer of III-V coupons to a silicon photonic target wafer. High Energy Computed Tomographic Inspection of Munitions Inspection system provides additional level of quality assurance for R&D, reverse engineering, and malfunction investigations. Terahertz (THz) Radar: A Solution for Degraded Visibility Environments (DVE) Operating at higher frequencies than other types of radar produces tighter beams and finer resolution. Imaging Detonations of Explosives Using high-speed camera pyrometers to measure and map fireball/shock expansion velocities.

Airborne Inspection Sensor Evolves with LiDAR, Mid-IR and Artificial Intelligence Air Force eVTOL Research and Development Programs Make Remote Pilot Progress Creating a Digital Gateway for RF Domain Will Advance Designs That Meet DoD Initiatives Understanding the Unique RF Interconnect Requirements for Ultra-Demanding Hypersonic Missile and Satellite Applications ADS-B Classification Using Multivariate Long Short-Term Memory This analysis extends previous research that used long short-term memory-fully convolutional networks to identify aircraft engine types from publicly available automatic dependent surveillance-broadcast (ADS-B) data.

Coastal Lidar and Radar Imaging System (CLARIS) Lidar Data Report An analysis of shoreline change, dune volume, beach volume, beach slope, and cumulative elevation change along the northern Outer Banks of North Carolina near the CHL Field Research Facility over a 6-year study period.

Fastener industry on fast track of change Technologies developed for fastening of metal aerospace parts are being transferred for bonding of composite parts. Moving toward sensor standardization One of the challenges facing aerospace developers is getting accurate test data from the many sensors used to monitor performance, simplifying setup and calibration. Wing design opens the envelope Technology presented at ACE describes a design process for a lightweight wing with an aerodynamic shape that is optimal for a large part of the cruise flight.

These methods use the vehicle’s current heading and generate a light detection and ranging (LIDAR) view through rectangular box regions. These box regions mimic the actual vision sensor regions, and logic can easily be applied to real vehicle conditions.

The newly operational American Center for Mobility (ACM), designed for all-weather testing of connected and autonomous vehicles, will use Microsoft as its data infrastructure and cloud resources provider.

More than 90% of new vehicles include Advanced Driving Assistance Systems that offer features such as Lane Keep Assist and Adaptive Cruise Control [1]. These ever-improving vehicle systems present a great opportunity to increase driving safety and reduce the number of roadway deaths and injuries. Indeed, they are already having a positive effect. However, the wide variety of features offered in the marketplace can be confusing to consumers, who may not clearly understand their vehicles’ true capabilities and limitations, or have an easy way of comparing system performance between vehicle models. This lack of information has the potential to reduce the safety gains of ADAS features by increasing the risk of improper use. To encourage transparency in the marketplace and thus engender the maximum positive effect of ADAS technologies, this paper proposes a five-level rating system, which utilizes diamonds to denote significant milestone achievements in vehicle system performance.

Intelligent driving, aimed for collision avoidance and self-navigation, is mainly based on environmental sensing via radar, lidar and/or camera. While each of the sensors has its own unique pros and cons, camera is especially good at object detection, recognition and tracking.

The sensors used in this study were one camera and one LiDAR. These sensors were connected to an NVIDIA Drive Px2 which operated in a 2019 Kia Niro. Two custom scenarios (static and dynamic objects) were chosen to collect sensor data operating in four real-world weather conditions: fair, cloudy, rainy, and light snow.

The reliability of an ADS’s environment perception provided by lidar, radar, and camera sensors is of special interest in this context, because perception errors can be safety-critical.