Sensing and Control for Autonomous Vehicles: Applications to Land, Water and Air

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This edited volume includes thoroughly collected on sensing and control for autonomous vehicles. Guidance, navigation and motion control systems for autonomous vehicles are increasingly important in land-based, marine and aerial operations. Autonomous underwater vehicles may be used for pipeline in
About this series This series aims to report new developments in the fields of control and information sciences-quickly, informally and at a high level. The type of material considered for publication includes 1. Preliminary drafts of monographs and advanced textbooks 2. Lectures on a new field, or presenting a new angle on a classical field 3. Research reports 4. Reports of meetings, provided they are (a) of exceptional interest and (b)devoted to a specific topic. The timeliness of subject material is very Important Moreinformationaboutthisseriesathttp://www.springer.com/series/642 Thor I. Fossen. Kristin y. pettersen Henk nijmeijer Editors Sensing and control for autonomous vehicles pplications to Land, water and air vehicles 空 Springer editors Thor l fossen Henk niimeijer norwegian University of Science and Eindhoven University of Technology( tuE) Technology (NTNU) Eindhoven Trondheim The netherlands Kristin y pettersen Norwegian University of Science and Technology (NTNU) Trondheim Norway ISSN0170-8643 issn 1610-7411(electronic) Lecture notes in Control and Information sciences ISBN978-3-319-55371-9 ISBN978-3-31955372-6( e Book) DOⅠ10.1007/978-3-319-55372-6 Library of Congress Control Number: 2017934064 C Springer International Publishing AG 2017 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, express or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations Printed on acid-free paper This Springer imprint is published by Springer Nature The registered company is Springer International Publishing AG The registered company address is: Gewerbestrasse ll, 6330 Cham, Switzerland Preface Sensing and Control for Autonomous Vehicles: Applications to Land, Water and Air Vehicles contains a collection of contributions presented at an invited workshop with the same name held June 20-22, 2017 in Alesund, Norway. The subject of the book is sensing and control with applications to autonomous vehicles. Guidance, navigation and motion control systems for autonomous vehicles are increasingly important in land-based, marine and aerial operations. Autonomous underwater vehicles may be used for pipeline inspection, light-intervention work underwater survey, and collection of oceanographic/biological data. Autonomous aerial and ground vehicles can be used in a large number of applications such as inspection, monitoring, data collection, surveillance, etc. At present, vehicles operate with limited autonomy and intelligence There is a growing interest for cooperative and coordinated multi-vehicle systems, localization and mapping, path planning, robust autonomous navigation systems and robust autonomous control of vehicles Unmanned vehicles with high levels of autonomy may be used for safe and efficient collection of environmental data. for assimilation of climate and environmental models and to complement global satellite systems With an appropriate balance between mathematical theory and practical appli- cations, academic and industrial researchers working on sensing and control engineering aspects of autonomous vehicles will benefit from this comprehensive book. It is also suitable for final year undergraduates and postgraduates, lecturers development officers, and practitioners in the areas of guidance, navigation and control of autonomous vehicles Preface Acknowledgements We are grateful to our sponsors Center for Autonomous Marine Operations and Systems (NTNU AMOS) at the Norwegian University of Science and Technology, Trondheim, Norway Norwegian Research Council grant no. 223254) Rolls-Royce Marine, Alesund, Norway Trondheim, Norway Thor. fossen Trondheim norway Kristin y pettersen Eindhoven. The Netherlands Henk niimeijer Contents PartI Vehicle Navigation Systems Observers for Position Estimation Using Bearing and Biased Ⅴ elocity Information Florent Le bras, Tarek Hamel, Robert mahony and claude samson Nonlinear Camera- and GNsS-Aided INS for Fixed-Wing UAV Using the eXogenous Kalman Filter 25 Lorenzo fusini Thor l fossen and Tor arne johansen Motion Control of RoVs for Mapping of Steep Underwater Walls 51 Stein M. nornes, Asgeir Sorensen and Martin ludvigsen Part II Localization and Mapping Underwater 3D Laser Scanners: The Deformation of the plane 73 Albert Palomer, Pere Ridao, David Ribas and Josep Forest Advances in Platforms and algorithms for high resolution Mapping in the marine environment 80 R. Thomas Sayre-McCord, Chris Murphy, jeffrey Kaeli, Clayton Kunz Peter Kimball and Hanumant Singh New Design Techniques for Globally Convergent Simultaneous Localization and Mapping: Analysis and Implementation Pedro Lourenco, Bruno Guerreiro, Pedro Batista, Paulo oliveira and carlos silvestre Pose-Graph SLAM for Underwater Navigation 143 Stephen M. Chaves, Enric Galceran, Paul Ozog, Jeffrey M. Walls and Ryan m. eustice VI ontent Exploring New Localization Applications Using a Smartphone 16l Fredrik Gustafsson and Gustaf Hendeby Part III Path Planning Model-Based Path Planning 183 Artur Wolek and Craig A. Woolsey Constrained Optimal motion Planning for Autonomous Vehicles Using PRONTO 207 A. Pedro Aguiar, Florian A. Bayer, John Hauser, Andreas J. Hausler Giuseppe Notarstefano, Antonio M. Pascoal, Alessandro rucco and alessandro sacco Part Iv Sensing and Tracking Systems Observability-Based Sensor Sampling 229 Kristi A. Morgansen and Natalie brace Tracking Multiple ground Objects Using a Team of Unmanned Air vehicles Joshua y. sakamaki. Randal w. beard and michael rice A Target Tracking System for AsV Collision Avoidance based on the pdaF Erik f. wilthil. andreas l. flaten and edmund f. brekke Detection and Tracking of Floating Objects Using a UAV with Thermal camera 289 Hakon hagen helgesen, Frederik Stendahl Leira, Tor Arne Johansen and Thor l. fossen Part v Identification and Motion Control of robotic vehicles Experimental Identification of Three Degree-of-Freedom Coupled Dynamic Plant Models for Underwater Vehicles 319 Stephen C. Martin and Louis L. Whitcomb Model-Based LOS Path-Following Control of Planar Underwater Snake robots 343 Anna m. Kohl. Eleni Kelasidi, Kristin Y. pettersen and Jan Tommy Gravdahl Robotized underwater Interventions Giuseppe casalino, Enrico Simetti and francesco Wanderlingh Contents Adaptive Training of Neural Networks for Control of Autonomous Mobile robots 387 Erik steur, Thijs Vromen and Henk nijmeijer Modeling, Identification and Control of High-Speed AsVs: Theory and Experiments 407 Bjorn-Olav holtung Eriksen and Morten Breivik Part Vi Coordinated and Cooperative Control of Multi-vehicle Systems From Cooperative to autonomous vehicles 435 Tom van der sande and henk nijmeijer Coordination of Multi-agent Systems with Intermittent Access to a Cloud repository 453 Antonio adaldo. Davide Liuzza. Dimos v. dimarogonas and Karl h. johansson A Sampled-Data Model Predictive Framework for Cooperative Path Following of Multiple robotic vehicles 473 A. Pedro aguiar, Alessandro rucco and Andrea Alessandretti Coordinated Control of Mobile Robots with Delay Compensation Based on Synchronization 495 Yiran Cao and Toshiki oguchi Index 515

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