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Autonomous Mobile Systems for Long-Term Operations in Spatio-Temporal Environments Cedric Pradalier

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Autonomous Mobile Systems for Long-Term Operations in Spatio-Temporal Environments Cedric Pradalier Autonomous Mobile Systems for Long-Term Operations in Spatio-Temporal Environments Cedric Pradalier To cite this version: Cedric Pradalier. Autonomous Mobile Systems for Long-Term Operations in Spatio-Temporal Envi- ronments. Robotics [cs.RO]. INP DE TOULOUSE, 2015. tel-01435879 HAL Id: tel-01435879 https://hal.archives-ouvertes.fr/tel-01435879 Submitted on 20 Jan 2017 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. Distributed under a Creative Commons Attribution| 4.0 International License Autonomous Mobile Systems for Long-Term Operations in Spatio-Temporal Environments Synth`ese des travaux de recherche r´ealis´es en vue de l’obtention de l’Habilitation `aDiriger des Recherches de l’Institut National Polytechnique de Toulouse C´edric PRADALIER GeorgiaTech Lorraine – UMI 2958 GT-CNRS 2, rue Marconi 57070 METZ, France [email protected] Soutenue le Vendredi 6 Juin 2015 au LAAS/CNRS Membres du jury: Francois Chaumette, INRIA, Rapporteur Tim Barfoot, University of Toronto, Rapporteur Henrik Christensen, Georgia Institute of Technology, Rapporteur Olivier Simonin, INSA Lyon, Examinateur Roland Lenain, IRSTEA, Examinateur Florent Lamiraux, LAAS/CNRS, Examinateur Simon Lacroix, LAAS/CNRS, Examinateur Contents 1 Introduction 2 2 Autonomous mobile systems for natural and unmodified environments 4 2.1 Localization, navigation and control for mobile robotic systems . 4 2.2 Challenging perception systems .......................... 9 2.3 Systems for environment observation ....................... 13 3 Perspectives: Towards observation and operations in spatio-temporal envi- ronments 17 3.1 Applications ..................................... 17 3.2 Challenges and Research Directions ........................ 18 3.3 Initial Results .................................... 22 3.4 Conclusion ..................................... 32 A Liu et al. [2013] 37 B Garneau et al. [2013] 51 C Stumm et al. [2012] 67 D Krebs et al. [2010a] 93 E Pradalier et al. [2008] 117 F Pradalier and Usher [2008] 143 G Pradalier et al. [2005] 166 H Curriculum Vitae 193 1 Chapter 1 Introduction This document reports on research conducted between 2001 and 2015 in the field of au- tonomous mobile robotics, specifically in what became known “field robotics”: a focus of robotics on outdoor, little-structured environments close to industrial applications. Chap- ter 2 describes a number of research projects, starting with activities initiated during my doctorate research at INRIA between 2001 and 2004, followed by a post-doctoral fellowship at CSIRO, in Canberra and Brisbane, Australia between 2004 and 2007. From 2007 to 2012, my role as Deputy-Director of the Autonomous Systems Lab at ETH Z¨urich, Switzerland, gave me the opportunity to supervise a number of projects ranging from space robotics and mechatronic design to European projects on indoor navigation or autonomous driving. On the other hand, chapter 3 will describe my reseach plan stemming from this experience and preliminary results from projects started in my current position as Associate Professor at GeorgiaTech Lorraine, the French campus of the Georgia Institute of Technology, also known as GeorgiaTech, located in Atlanta, USA. This research has been published in a number of journal publications which will support our synthesis. A selection of these publications is attached at the end of this report and will be described in more details in chapter 2: 1. Ming Liu, C´edric Pradalier, and Roland Siegwart. Visual homing from scale with an uncalibrated omnidirectional camera. IEEE Transaction on Robotics, (99):1–13, 2013 – Appendix A 2. Marie-Eve` Garneau, Thomas Posch, Gregory Hitz, Fran¸cois Pomerleau, C´edric Pradalier, Roland Siegwart, and Jakob Pernthaler. Short-term displacement of planktothrix rubescens (cyanobacteria) in a pre-alpine lake observed using an autonomous sampling platform. Limnography and Oceanography, 58(5), 2013 – Appendix B 3. Elena Stumm, Andreas Breitenmoser, Francois Pomerleau, Cedric Pradalier, and Roland Siegwart. Tensor voting based navigation for robotic inspection of 3d surfaces using lidar point clouds. The International Journal of Robotics Research, 31(11), 2012 – Ap- pendix C 4. Ambroise Krebs, C´edric Pradalier, and Roland Siegwart. Adaptive rover behavior based on online empirical evaluation: Rover–terrain interaction and near-to-far learning. Jour- nal of Field Robotics, 27(2):158–180, 2010a – Appendix D 2 5. C´edric Pradalier, Ashley Tews, and Jonathan Roberts. Vision-based operations of a large industrial vehicle: Autonomous hot metal carrier. Journal of Field Robotics, 25 (4-5):243–267, 2008 – Appendix E 6. C´edric Pradalier and Kane Usher. Robust trajectory tracking for a reversing tractor trailer. Journal of Field Robotics, 25(6-7):378–399, 2008 – Appendix F 7. C´edric Pradalier, Jorge Hermosillo, Carla Koike, Christophe Braillon, Pierre Bessi`ere, and Christian Laugier. The cycab: a car-like robot navigating autonomously and safely among pedestrians. Robotics and Autonomous Systems, 50(1):51–67, 2005 – Appendix G Out of this body of work, three main themes can be separated: the development of navigation systems for various robotic systems in a deployment context [Liu et al., 2013, Stumm et al., 2012, Krebs et al., 2010a, Pradalier et al., 2008, Pradalier and Usher, 2008, Pradalier et al., 2005], the development of solutions to challenging perception problems in natural environ- ments, mostly using vision [Liu et al., 2013, Krebs et al., 2010a, Pradalier et al., 2008, 2005] and the design of autonomous mobile systems for the monitoring of natural and industrial environments [Garneau et al., 2013, Hitz et al., 2012, Negre et al., 2008]. Chapter 2 will present more details about these themes and link them to demonstrate how they converge to a common research question: how to design efficient and robust autonomous mobile systems for natural and unmodified environments, while taking into account the constraints resulting from the need to deploy and evaluate these systems in the field. From mobility and monitoring in natural unstructured system, our research is now evolving towards long-term observation of large-scale environments subjected to changes on different time scale. The environments we are considering here can be described on a multi-kilometer scale but may require centimeters of precision in their representation, at least locally (de- pending on the task). In these environments, change is expected to happen at scales varying from seconds to years depending on the natural processes at play. Chapter 3 will provide some insight on our current research and long-term perspectives. 3 Chapter 2 Autonomous mobile systems for natural and unmodified environments 2.1 Localization, navigation and control for mobile robotic systems Designing the software architecture for mobile robotic systems involves, most of the times, the dedication of a significant share of the work to the problems of localization, navigation and multiple layers of control. This section will succinctly describe the systems we implemented on some of the robotic systems we encountered in the last 15 years, in France, Switzerland and Australia 2.1.1 CyCab: Navigation among pedestrians Figure 2.1: The CyCab: an autonomous car-like vehicle for urban mobility The CyCab (figure 2.1) is a small autonomous car-like vehicle. Its specificity is its ability to steer both front and rear axle, giving it an excellent maneuverability well suited for urban 4 environments. The work presented in Pradalier et al. [2005], Cou´eet al. [2006], Pradalier and Bessi`ere [2008] was conducted at INRIA Rhone-Alpes (Grenoble) between 2001 and 2004. Autonomous navigation with the CyCab required to first solve the problems of localization and mapping for which we presented an original approach [Pradalier and Sekhavat, 2002] based on the identification of invariant features in the measurement process. From then on, with the collaboration of J. Hermosillo, we could integrate a global planner accounting for the dual-steering capability of the vehicle and an obstacle avoidance system built on a probabilistic framework. The fully integrated systems was presented in Pradalier et al. [2005] as well as in a number of public demonstrations. 2.1.2 The Hot Metal Carrier Figure 2.2: The Hot Metal Carrier, a modified forklift for the transport of liquid aluminium Our work on the Hot Metal Carrier (HMC, see figure 2.2) took place at the CSIRO1 in Brisbane, Australia, between 2004 and 2007. Its summary is presented in Pradalier et al. [2008]. For this system, the challenges were to develop a localization and navigation system, the control layers, and most importantly vision-based load handling. The latter is the main contribution in Pradalier et al. [2008]. Based on markers on the load and a vision-based state estimator, the 6-meter long vehicle could insert its hook into the lifting ring of the crucible with better than 5cm of precision and an excellent repeatability. Because of its industrial nature, this project put a particular focus on robustness and a significant
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