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The Canadian planetary emulation terrain 3D mapping dataset

INTERNATIONAL JOURNAL OF robotics RESEARCH 2013年第4期32卷 389-395页

作者： Tong, Chi Hay Gingras, David Larose, Kevin Barfoot, Timothy D. Dupuis, Erick Univ Toronto Inst Aerosp Studies Toronto ON M5S 1A1 Canada Canadian Space Agcy Space Explorat Grp Toronto ON Canada

This paper describes a collection of 272 three-dimensional laser scans gathered at two unique planetary analogue rover test facilities in Canada, which offer emulated planetary terrain at manageable scales for algorithmic development. This dataset is subdivided into four individual subsets, each gathered using panning laser rangefinders on different mobile rover platforms. This data should be of interest to field robotics researchers developing rover navigation algorithms suitable for use in three-dimensional, unstructured, natural terrain. All of the data are presented in human-readable text files, and are accompanied by Matlab parsing scripts to facilitate use thereof. This paper provides an overview of the available data.

关键词： mobile and distributed robotics slam space robotics field and service robotics

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Real-time pose estimation of a dynamic quadruped in GPS-denied environments for 24-hour operation

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INTERNATIONAL JOURNAL OF robotics RESEARCH 2016年第6期35卷 631-653页

作者： Ma, Jeremy Bajracharya, Max Susca, Sara Matthies, Larry Malchano, Matt CALTECH Jet Prop Lab Pasadena CA 91125 USA Google Mountain View CA USA Boston Dynam Waltham MA USA

We present a real-time system that enables a highly capable dynamic quadruped robot to maintain an accurate six-degree-of-freedom pose estimate (within a 1.0% error of distance traveled) over long distances traversed through complex, dynamic outdoor terrain, during day and night, in the presence of camera occlusion and saturation, and occasional large external disturbances, such as slips or falls. The system fuses a stereo-camera sensor, inertial measurement unit, leg odometry, and optional intermittent GPS position updates with an extended Kalman filter to ensure robust, low-latency performance. To maintain a six-degree-of-freedom local positioning accuracy alongside the global positioning knowledge, two reference frames are used;a local reference frame and a global reference frame, with the former benefiting obstacle detection and mapping and the latter for operator-specified and autonomous way-point following. Extensive experimental results obtained from multiple field tests are presented to illustrate the performance and robustness of the system over hours of continuous runs and hundreds of kilometers of distance traveled in a wide variety of terrains and conditions.

关键词： Localization mobile and distributed robotics slam sensor fusion sensing and perception computer vision legged robots mechanics design and control field robots field and service robotics visual tracking sensing and perception computer vision

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3D Mapping for high-fidelity unmanned ground vehicle lidar simulation

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INTERNATIONAL JOURNAL OF robotics RESEARCH 2012年第12期31卷 1349-1376页

作者： Browning, Brett Deschaud, Jean-Emmanuel Prasser, David Rander, Peter Carnegie Mellon Univ Inst Robot Natl Robot Engn Ctr Pittsburgh PA 15201 USA

High-fidelity simulation is a key enabling technology for the widespread deployment of large unmanned ground vehicles (UGVs). However, current approaches for lidar simulation leave much to be desired, particularly for scenes with vegetation. We introduce a novel 3D mapping technique that learns high-fidelity models for geo-specific lidar simulation directly from pose tagged lidar data. We introduce a novel stochastic, volumetric model that captures and can reproduce the statistical interactions of lidar with terrain. We show how to automatically learn the model directly from 3D mapping data collected by a UGV in the target environment. We extend our approach using terrain-classification techniques to develop a hybrid surface-volumetric model that combines the efficiency of surface modeling for areas that are well approximated by large surfaces (e.g. roads, bare earth) with our volumetric approach for more complex areas (e.g. bushes, trees) without sacrificing overall fidelity. We quantitatively compare the performance of our approach against more conventional methods on large outdoor datasets from urban and off-road environments. Our results show significant performance gains using our volumetric and hybrid approaches over the state-of-the-art, laying the ground work for truly high-fidelity simulation engines for UGVs.

关键词： Mapping mobile and distributed robotics slam range sensing sensing and perception computer vision animation and simulation simulation interfaces and virtual reality field robots field and service robotics

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A High-rate, Heterogeneous Data Set From The DARPA Urban Challenge

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INTERNATIONAL JOURNAL OF robotics RESEARCH 2010年第13期29卷 1595-1601页

作者： Huang, Albert S. Antone, Matthew Olson, Edwin Fletcher, Luke Moore, David Teller, Seth Leonard, John MIT CSAIL Cambridge MA USA BAE Syst Burlington MA USA Univ Michigan Ann Arbor MI 48109 USA

This paper describes a data set collected by MIT's autonomous vehicle Talos during the 2007 DARPA Urban Challenge. Data from a high-precision navigation system, five cameras, 12 SICK planar laser range scanners, and a Velodyne high-density laser range scanner were synchronized and logged to disk for 90 km of travel. In addition to documenting a number of large loop closures useful for developing mapping and localization algorithms, this data set also records the first robotic traffic jam and two autonomous vehicle collisions. It is our hope that this data set will be useful to the autonomous vehicle community, especially those developing robotic perception capabilities.

关键词： mobile and distributed robotics slam sensing and perception computer vision field and service robotics

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An Ultrasound-based Localization Algorithm for Catheter Ablation Guidance in the Left Atrium

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INTERNATIONAL JOURNAL OF robotics RESEARCH 2010年第6期29卷 643-665页

作者： Koolwal, Aditya Brij Barbagli, Federico Carlson, Christopher Liang, David Stanford Univ Dept Mech Engn Stanford CA 94305 USA Stanford Univ Dept Comp Sci Stanford CA 94305 USA Hansen Med Inc Mountain View CA 94043 USA Stanford Sch Med Dept Cardiovasc Med Falk Cardiovasc Res Ctr Stanford CA 94305 USA

We present a method for catheter localization in the left atrium based on the unscented particle filter (UPF), a Monte Carlo method employed in stochastic state estimation. Using an intracardiac echo (ICE) ultrasound catheter, we acquire ultrasound images of the atrium from multiple configurations and iteratively determine the catheter's pose with respect to anatomy. At each time step, the catheter's change in pose is determined using either a six-degree-of-freedom electromagnetic pose sensor or a robotic guide catheter whose kinematics serve as a pseudo-pose measurement. Sensor and kinematic model uncertainties are explicitly considered when computing the localization estimate. Acquired ultrasound images are compared with simulated ultrasound images based on segmented computed tomography (CT) or magnetic resonance (MR) data of the left atrium. The results of these comparisons are used to refine the localization estimate. After considering less than 30 seconds' worth of ICE data, our algorithm converges to an accurate pose estimate. Furthermore, our algorithm is robust to sensor drift and kinematic model errors, as well as gradual, unmodeled movements in the anatomy. Such problems typically complicate traditional image-based localization.

关键词： medical robots and systems human-centered and lifelike robotics localization mobile and distributed robotics slam sensor fusion sensing and perception computer vision

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Learning Combinatorial Map Information from Permutations of Landmarks

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INTERNATIONAL JOURNAL OF robotics RESEARCH 2011年第9期30卷 1143-1156页

作者： Tovar, Benjamin Freda, Luigi LaValle, Steven M. Northwestern Univ Dept Mech Engn Evanston IL 60208 USA UTRI SpA Trieste Trieste Italy Univ Illinois Dept Comp Sci Urbana IL 61801 USA

This paper considers a robot that moves in the plane and that is able to sense only the cyclic order of landmarks with respect to its current position. No metric information is available regarding the robot or landmark positions;moreover, the robot does not have a compass or odometers (i.e., knowledge of coordinates). We carefully study the information space of the robot, and establish its capabilities in terms of mapping the environment and accomplishing tasks, such as navigation and patrolling. When the robot moves exclusively inside the perimeter of the set of landmarks, the information space may be succinctly characterized as an order type that provides information powerful enough to determine which points lie inside the convex hulls of subsets of landmarks. In addition, if the robot is allowed to move outside the perimeter of the set of landmarks, the information space is described with a swap cell decomposition, that is, an aspect graph in which each aspect is a cyclic permutation of landmarks. Finally, we show how to construct such decomposition through its dual, using two kinds of feedback motion commands based on the landmarks sensed.

关键词： Mapping mobile and distributed robotics slam localization learning and adaptive systems cognitive robotics

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Continuous-time batch trajectory estimation using temporal basis functions

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INTERNATIONAL JOURNAL OF robotics RESEARCH 2015年第14期34卷 1688-1710页

作者： Furgale, Paul Tong, Chi Hay Barfoot, Timothy D. Sibley, Gabe ETH CH-8049 Zurich Switzerland Univ Oxford Oxford England Univ Toronto Toronto ON Canada Univ Colorado Boulder CO 80309 USA

Roboticists often formulate estimation problems in discrete time for the practical reason of keeping the state size tractable;however, the discrete-time approach does not scale well for use with high-rate sensors, such as inertial measurement units, rolling-shutter cameras, or sweeping laser imaging sensors. The difficulty lies in the fact that a pose variable is typically included for every time at which a measurement is acquired, rendering the dimension of the state impractically large for large numbers of measurements. This issue is exacerbated for the simultaneous localization and mapping problem, which further augments the state to include landmark variables. To address this tractability issue, we propose to move the full Maximum-a-Posteriori estimation problem into continuous time and use temporal basis functions to keep the state size manageable. We present a full probabilistic derivation of the continuous-time estimation problem, derive an estimator based on the assumption that the densities and processes involved are Gaussian and show how the coefficients of a relatively small number of basis functions can form the state to be estimated, making the solution efficient. Our derivation is presented in steps of increasingly specific assumptions, opening the door to the development of other novel continuous-time estimation algorithms through the application of different assumptions at any point. We use the simultaneous localization and mapping problem as our motivation throughout the paper, although the approach is not specific to this application. Results from two experiments are provided to validate the approach: (i) self-calibration involving a camera and a high-rate inertial measurement unit, and (ii) perspective localization with a rolling-shutter camera.

关键词： Sensor fusion sensing and perception computer vision localization mobile and distributed robotics slam mapping

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Modeling and Control of UAV Bearing Formations with Bilateral High-level Steering

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INTERNATIONAL JOURNAL OF robotics RESEARCH 2012年第12期31卷 1504-1525页

作者： Franchi, Antonio Masone, Carlo Grabe, Volker Ryll, Markus Buelthoff, Heinrich H. Giordano, Paolo Robuffo Max Planck Inst Biol Cybernet D-72076 Tubingen Germany Korea Univ Dept Brain & Cognit Sci Seoul South Korea

In this paper we address the problem of controlling the motion of a group of unmanned aerial vehicles (UAVs) bound to keep a formation defined in terms of only relative angles (i.e. a bearing formation). This problem can naturally arise within the context of several multi-robot applications such as, e. g. exploration, coverage, and surveillance. First, we introduce and thoroughly analyze the concept and properties of bearing formations, and provide a class of minimally linear sets of bearings sufficient to uniquely define such formations. We then propose a bearing-only formation controller requiring only bearing measurements, converging almost globally, and maintaining bounded inter-agent distances despite the lack of direct metric information. The controller still leaves the possibility of imposing group motions tangent to the current bearing formation. These can be either autonomously chosen by the robots because of any additional task (e. g. exploration), or exploited by an assisting human co-operator. For this latter 'human-in-the-loop' case, we propose a multi-master/multi-slave bilateral shared control system providing the co-operator with some suitable force cues informative of the UAV performance. The proposed theoretical framework is extensively validated by means of simulations and experiments with quadrotor UAVs equipped with onboard cameras. Practical limitations, e. g. limited field-of-view, are also considered.

关键词： Networked robots mobile and distributed robotics slam telerobotics simulation interfaces and virtual reality aerial robotics field and service robotics distributed robot systems surveillance systems sensing and perception computer vision

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Real-time Bounded-error State Estimation for Vehicle Tracking

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INTERNATIONAL JOURNAL OF robotics RESEARCH 2009年第1期28卷 34-48页

作者： Seignez, E. Kieffer, M. Lambert, A. Walter, E. Maurin, T. Univ Paris 11 CNRS Inst Elect Fondamentale F-91400 Orsay France Supelec Univ Paris Sud CNRS Signaux & Syst Lab F-91192 Gif Sur Yvette France

Estimating the configuration of a vehicle is crucial for its navigation. Most approaches are based on (extended) Kalman filtering or particle filtering. An attractive alternative is considered here, which relies on interval analysis. Contrary to classical extended Kalman filtering it allows global localization, and contrary to particle filtering it provides guaranteed results in the sense that a set is computed that contains all of the configurations that are consistent with the data and hypotheses. This paper presents a real-time implementation of the process including a description of the platform and its modeling, the integration of the errors on the model and the localization method itself.

关键词： Autonomous agents cognitive robotics wheeled robots mechanics design and control localization mobile and distributed robotics slam range sensing sensing and perception computer vision

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Cooperative AUV Navigation using a Single Maneuvering Surface Craft

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INTERNATIONAL JOURNAL OF robotics RESEARCH 2010年第12期29卷 1461-1474页

作者： Fallon, Maurice F. Papadopoulos, Georgios Leonard, John J. Patrikalakis, Nicholas M. MIT Comp Sci & Artificial Intelligence Lab Cambridge MA 02139 USA

In this paper we describe the experimental implementation of an online algorithm for cooperative localization of submerged autonomous underwater vehicles (AUVs) supported by an autonomous surface craft. Maintaining accurate localization of an AUV is difficult because electronic signals, such as GPS, are highly attenuated by water. The usual solution to the problem is to utilize expensive navigation sensors to slow the rate of dead-reckoning divergence. We investigate an alternative approach that utilizes the position information of a surface vehicle to bound the error and uncertainty of the on-board position estimates of a low-cost AUV. This approach uses the Woods Hole Oceanographic Institution (WHOI) acoustic modem to exchange vehicle location estimates while simultaneously estimating inter-vehicle range. A study of the system observability is presented so as to motivate both the choice of filtering approach and surface vehicle path planning. The first contribution of this paper is to the presentation of an experiment in which an extended Kalman filter (EKF) implementation of the concept ran online on-board an OceanServer Iver2 AUV while supported by an autonomous surface vehicle moving adaptively. The second contribution of this paper is to provide a quantitative performance comparison of three estimators: particle filtering (PF), non-linear least-squares optimization (NLS), and the EKF for a mission using three autonomous surface craft (two operating in the AUV role). Our results indicate that the PF and NLS estimators outperform the EKF, with NLS providing the best performance.

关键词： Marine robotics field and service robotics motion control mobile and distributed robotics slam range sensing path planning for multiple mobile robot systems mechanics design and control localization

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