In this paper, we study estimator inconsistency in vision-aided inertial navigation systems (VINS) from the standpoint of system's observability. We postulate that a leading cause of inconsistency is the gain of spurious information along unobservable directions, which results in smaller uncertainties, larger estimation errors, and divergence. We develop an observability constrained VINS (OC-VINS), which explicitly enforces the unobservable directions of the system, hence preventing spurious information gain and reducing inconsistency. This framework is applicable to several variants of the VINS problem such as visual simultaneous localization and mapping (V-SLAM), as well as visual-inertial odometry using the multi-state constraint Kalman filter (MSC-KF). Our analysis, along with the proposed method to reduce inconsistency, are extensively validated with simulation trials and real-world experimentation.

/pdf/consistency-analysis-and-improvement-of-vision-aided-26tv9hnuka.pdf

Consistency Analysis and Improvement of Vision-aided Inertial Navigation

Mobile LiDAR technology is currently one of the attractive topics in the fields of remote sensing and laser scanning. Mobile LiDAR enables a rapid collection of enormous volumes of highly dense, irregularly distributed, accurate geo-referenced data, in the form of three-dimensional (3D) point clouds. This technology has been gaining popularity in the recognition of roads and road-scene objects. A thorough review of available literature is conducted to inform the advancements in mobile LiDAR technologies and their applications in road information inventory. The literature review starts with a brief overview of mobile LiDAR technology, including system components, direct geo-referencing, data error analysis and geometrical accuracy validation. Then, this review presents a more in-depth description of current mobile LiDAR studies on road information inventory, including the detection and extraction of road surfaces, small structures on the road surfaces and pole-like objects. Finally, the challenges ...

Use of mobile LiDAR in road information inventory: a review

A thorough review of available literature was conducted to inform of advancements in mobile LIDAR technology, techniques, and current and emerging applications in transportation. The literature review touches briefly on the basics of LIDAR technology followed by a more in depth description of current mobile LIDAR trends, including system components and software. An overview of existing quality control procedures used to verify the accuracy of the collected data is presented. A collection of case studies provides a clear description of the advantages of mobile LIDAR, including an increase in safety and efficiency. The final sections of the review identify current challenges the industry is facing, the guidelines that currently exist, and what else is needed to streamline the adoption of mobile LIDAR by transportation agencies. Unfortunately, many of these guidelines do not cover the specific challenges and concerns of mobile LIDAR use as many have been developed for airborne LIDAR acquisition and processing. From this review, there is a lot of discussion on “what” is being done in practice, but not a lot on “how” and “how well” it is being done. A willingness to share information going forward will be important for the successful use of mobile LIDAR.

https://ir.library.oregonstate.edu/downloads/1v53jz63h

Synthesis of Transportation Applications of Mobile LIDAR

This paper presents a survey of literature about road feature extraction, giving a detailed description of a Mobile Laser Scanning (MLS) system (RIEGL VMX-450) for transportation-related applications. This paper describes the development of automated algorithms for extracting road features (road surfaces, road markings, and pavement cracks) from MLS point cloud data. The proposed road surface extraction algorithm detects road curbs from a set of profiles that are sliced along vehicle trajectory data. Based on segmented road surface points, we create Geo-Referenced Feature (GRF) images and develop two algorithms, respectively, for extracting the following: 1) road markings with high retroreflectivity and 2) cracks containing low contrast with their surroundings, low signal-to-noise ratio, and poor continuity. A comprehensive comparison illustrates satisfactory performance of the proposed algorithms and concludes that MLS is a reliable and cost-effective alternative for rapid road inspection.

Automated Road Information Extraction From Mobile Laser Scanning Data

Newest developments in laser scanner technologies put surveyors in the position to comply with the ever increasing
demand of high-speed, high-accuracy, and highly reliable data acquisition from terrestrial, mobile, and airborne
platforms. Echo digitization in pulsed time-of-flight laser ranging has demonstrated its superior performance in the field
of bathymetry and airborne laser scanning for more than a decade, however at the cost of somewhat time consuming off
line post processing. State-of-the-art online waveform processing as implemented in RIEGL's V-Line not only saves
users post-processing time to obtain true 3D point clouds, it also adds the assets of calibrated amplitude and reflectance
measurement for data classification and pulse deviation determination for effective and reliable data validation. We
present results from data acquisitions in different complex target situations.

Improving quality of laser scanning data acquisition through calibrated amplitude and pulse deviation measurement

Abstract Mobile laser scanning (MLS) is the latest approach towards fast and cost-efficient acquisition of 3-dimensional spatial data. Accurately evaluating the boresight alignment in MLS systems is an obvious necessity. However, recent systems available on the market may lack of suitable and efficient practical workflows on how to perform this calibration. This paper discusses an innovative method for accurately determining the boresight alignment of MLS systems by employing 3D laser scanners. Scanning objects using a 3D laser scanner operating in a 2D line-scan mode from various different runs and scan directions provides valuable scan data for determining the angular alignment between inertial measurement unit and laser scanner. Field data is presented demonstrating the final accuracy of the calibration and the high quality of the point cloud acquired during an MLS campaign.

/pdf/boresight-alignment-method-for-mobile-laser-scanning-systems-no0c54v0kl.pdf

G. Zach

Papers

Boresight alignment method for mobile laser scanning systems