Deposits of clastic carbonate-dominated (calciclastic) sedimentary slope systems in the rock record have been identified mostly as linearly-consistent carbonate apron deposits, even though most ancient clastic carbonate slope deposits fit the submarine fan systems better. Calciclastic submarine fans are consequently rarely described and are poorly understood. Subsequently, very little is known especially in mud-dominated calciclastic submarine fan systems. Presented in this study are a sedimentological core and petrographic characterisation of samples from eleven boreholes from the Lower Carboniferous of Bowland Basin (Northwest England) that reveals a >250 m thick calciturbidite complex deposited in a calciclastic submarine fan setting. Seven facies are recognised from core and thin section characterisation and are grouped into three carbonate turbidite sequences. They include: 1) Calciturbidites, comprising mostly of highto low-density, wavy-laminated bioclast-rich facies; 2) low-density densite mudstones which are characterised by planar laminated and unlaminated muddominated facies; and 3) Calcidebrites which are muddy or hyper-concentrated debrisflow deposits occurring as poorly-sorted, chaotic, mud-supported floatstones. These

Phd by thesis

For many applications in Urban Search and Rescue (USAR) scenarios robots need to learn a map of unknown environments. We present a system for fast online learning of occupancy grid maps requiring low computational resources. It combines a robust scan matching approach using a LIDAR system with a 3D attitude estimation system based on inertial sensing. By using a fast approximation of map gradients and a multi-resolution grid, reliable localization and mapping capabilities in a variety of challenging environments are realized. Multiple datasets showing the applicability in an embedded hand-held mapping system are provided. We show that the system is sufficiently accurate as to not require explicit loop closing techniques in the considered scenarios. The software is available as an open source package for ROS.

A flexible and scalable SLAM system with full 3D motion estimation

Scan matching, the problem of registering two laser scans in order to determine the relative positions from which the scans were obtained, is one of the most heavily relied-upon tools for mobile robots. Current algorithms, in a trade-off for computational performance, employ heuristics in order to quickly compute an answer. Of course, these heuristics are imperfect: existing methods can produce poor results, particularly when the prior is weak. The computational power available to modern robots warrants a re-examination of these quality vs. complexity trade-offs. In this paper, we advocate a probabilistically-motivated scan-matching algorithm that produces higher quality and more robust results at the cost of additional computation time. We describe several novel implementations of this approach that achieve real-time performance on modern hardware, including a multi-resolution approach for conventional CPUs, and a parallel approach for graphics processing units (GPUs). We also provide an empirical evaluation of our methods and several contemporary methods, illustrating the benefits of our approach. The robustness of the methods make them especially useful for global loop-closing.

/pdf/real-time-correlative-scan-matching-52cmj9l5iq.pdf

Real-time correlative scan matching

https://eprints.lincoln.ac.uk/9321/1/zender2008ras.pdf

Conceptual spatial representations for indoor mobile robots

This paper presents an experimental evaluation of different line extraction algorithms on 2D laser scans for indoor environment. Six popular algorithms in mobile robotics and computer vision are selected and tested. Experiments are performed on 100 real data scans collected in an office environment with a map size of 80m /spl times/ 50m. Several comparison criteria are proposed and discussed to highlight the advantages and drawbacks of each algorithm, including speed, complexity, correctness and precision. The results of the algorithms are compared with the ground truth using standard statistical methods.

/pdf/a-comparison-of-line-extraction-algorithms-using-2d-laser-38hwyhrna3.pdf

A comparison of line extraction algorithms using 2D laser rangefinder for indoor mobile robotics

This paper presents a novel method for 2D laser scan matching called polar scan matching (PSM). The method belongs to the family of point to point matching approaches. Our method avoids searching for point associations by simply matching points with the same bearing. This association rule enables the construction of an algorithm faster than the iterative closest point (ICP). Firstly the PSM approach is tested with simulated laser scans. Then the accuracy of our matching algorithm is evaluated from real laser scans from known relative positions to establish a ground truth. Furthermore, to demonstrate the practical usability of the new PSM approach, experimental results from a Kalman filter implementation of simultaneous localization and mapping (SLAM) are provided.

/pdf/laser-scan-matching-in-polar-coordinates-with-application-to-y3uyly0f9u.pdf

Laser scan matching in polar coordinates with application to SLAM

In this paper a novel Polar Scan Matching (PSM) approach is described that works in the laser scanner's polar coordinate system, therefore taking advantage of the structure of the laser measurements and eliminating the need for an expensive search for corresponding points in other scan match approaches. PSM belongs to the family of point to point scan matching approaches with its matching bearing association rule. The performance of PSM is thoroughly evaluated in a simulated experiment, in experiments using ground truth, in experiments aimed at determining the area of convergence and in a SLAM experiment. All results are compared to results obtained using an iterated closest point (ICP) scan matching algorithm implementation. It is found that PSM is superior to the ICP implementation in processing speed and that PSM converges to a correct solution from a larger range of initial positions.

/pdf/fast-laser-scan-matching-using-polar-coordinates-41qex8yfg2.pdf

Fast Laser Scan Matching using Polar Coordinates

Increasing the information content of measurements can ease some of the problems associated with simultaneous localization and mapping (SLAM). We present an approach for combining measurements from a laser range finder with measurements from an advanced sonar array capable of accurate range and bearing measurements and edge, corner and plane classification. In our approach sonar aids laser segmentation, laser aids good sonar point feature selection and laser and sonar measurements of the same object are fused. We also present a novel approach for fitting right angle corners to laser range data, which enables simple error estimation through the minimization of sum of square range residuals. The results are then used for SLAM with a mobile robot.

/pdf/advanced-sonar-and-laser-range-finder-fusion-for-12hz9aspsr.pdf

Advanced sonar and laser range finder fusion for simultaneous localization and mapping

This paper presents a novel approach to mapping for mobile robots that exploits user interaction to semiautonomously create a labelled map of the environment. The robot autonomously follows the user and is provided with a verbal commentary on the current location with phrases such as “Robot, we are in the office”. At the same time, a metric feature map is generated using fusion of laser and advanced sonar measurements in a Kalman filter based SLAM framework, which is later used for localization. When mapping is complete, the robot generates an occupancy grid for use in global task planning. The occupancy grid is created using a novel laser scan registration scheme that relies on storing the path of the robot along with associated local SLAM features during mapping, and later recovering the path by matching the associated local features to the final SLAM map. The occupancy grid is segmented into labelled rooms using an algorithm based on watershed segmentation and integration of the verbal commentary. Experimental results demonstrate our mobile robot creating SLAM and segmented occupancy grid maps of rooms along a 70 metre corridor, and then using these maps to navigate between rooms.

/pdf/interactive-slam-using-laser-and-advanced-sonar-2r4110mwew.pdf

Interactive SLAM using Laser and Advanced Sonar

http://www.zemris.fer.hr/~ssegvic/pubs/cviu08.pdf

A. Diosi

Papers

Laser scan matching in polar coordinates with application to SLAM

Fast Laser Scan Matching using Polar Coordinates

Advanced sonar and laser range finder fusion for simultaneous localization and mapping

Interactive SLAM using Laser and Advanced Sonar

A mapping and localization framework for scalable appearance-based navigation