An ICP variant using a point-to-line metric

This paper describes PLICP, an ICP (iterative closest/corresponding point) variant that uses a point-to-line metric, and an exact closed-form for minimizing such metric. The resulting algorithm has some interesting properties: it converges quadratically, and in a finite number of steps. The method is validated against vanilla ICP, IDC (iterative dual correspondences), and MBICP (Metric-Based ICP) by reproducing the experiments performed in Minguez et al. (2006). The experiments suggest that PLICP is more precise, and requires less iterations. However, it is less robust to very large initial displacement errors. The last part of the paper is devoted to purely algorithmic optimization of the correspondence search; this allows for a significant speed-up of the computation. The source code is available for download

Stochastic cloning: a generalized framework for processing relative state measurements

Introduces a generalized framework, termed "stochastic cloning," for processing relative state measurements within a Kalman filter estimator. The main motivation and application for this methodology is the problem of fusing displacement measurements with position estimates for mobile robot localization. Previous approaches have ignored the developed interdependencies (cross-correlation terms) between state estimates of the same quantities at different time instants. By directly expressing relative state measurements in terms of previous and current state estimates, the effect of these crosscorrelation terms on the estimation process is analyzed and considered during updates. Simulation and experimental results validate this approach

2D LIDAR Aided INS for vehicle positioning in urban environments

This paper presents a novel method to utilize\textit{2D} LIDAR for INS (Inertial Navigation System) aiding to improve\textit{3D} vehicle position estimation accuracy, especially when GNSS signals are shadowed.In the proposed framework, 2D LIDAR aiding is carried out without imposing any assumptions on the vehicle motion (e.g. we allow full six degree-of freedom motion).To achieve this, a closed-form formula is derived to predict the line measurement in the LIDAR's frame.This makes the feature association, residual formation and GUI display possible.With this formula, the Extended Kalman Filter (EKF) can be employed in a straightforward manner to fuse the LIDAR and IMU data to estimate the full state of the vehicle.Preliminary experimental results show the effectiveness of the LIDAR aiding in reducing the state estimation uncertainty along certain directions, when GNSS signals are shadowed

A Review of Point Cloud Registration Algorithms for Mobile Robotics

International audienceThe topic of this review is geometric registration in robotics. Registration algorithms associate sets of data into a common coordinate system. They have been used extensively in object reconstruction, inspection, medical application, and localization of mobile robotics. We focus on mobile robotics applications in which point clouds are to be registered. While the underlying principle of those algorithms is simple, many variations have been proposed for many different applications. In this review, we give a historical perspective of the registration problem and show that the plethora of solutions can be organized and differentiated according to a few elements. Accordingly, we present a formalization of geometric registration and cast algorithms proposed in the literature into this framework. Finally, we review a few applications of this framework in mobile robotics that cover different kinds of platforms, environments, and tasks. These examples allow us to study the specific requirements of each use case and the necessary configuration choices leading to the registration implementation. Ultimately, the objective of this review is to provide guidelines for the choice of geometric registration configuration

Advances in Sonar Technology

The demand to explore the largest and also one of the richest parts of our planet, the advances in signal processing promoted by an exponential growth in computation power and a thorough study of sound propagation in the underwater realm, have lead to remarkable advances in sonar technology in the last years.The work on hand is a sum of knowledge of several authors who contributed in various aspects of sonar technology. This book intends to give a broad overview of the advances in sonar technology of the last years that resulted from the research effort of the authors in both sonar systems and their applications. It is intended for scientist and engineers from a variety of backgrounds and even those that never had contact with sonar technology before will find an easy introduction with the topics and principles exposed here