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Multi-robot coverage and exploration on Riemannian manifolds with boundaries

INTERNATIONAL JOURNAL OF robotics RESEARCH 2014年第1期33卷 113-137页

作者： Bhattacharya, Subhrajit Ghrist, Robert Kumar, Vijay Univ Penn Dept Math Philadelphia PA 19104 USA Univ Penn Dept Mech Engn & Appl Mech Philadelphia PA 19104 USA

Multi-robot coverage and exploration are fundamental problems in robotics. A widely used, efficient and distributable algorithm for achieving coverage of a convex environment with Euclidean metrics is that proposed by Cortes which is based on the discrete-time Lloyd's algorithm. This algorithm is not directly applicable to general Riemannian manifolds with boundaries that are non-convex and are intrinsically non-Euclidean. In this paper we generalize the control law based on minimization of the coverage functional to such non-Euclidean spaces punctured by obstacles. We also propose a practical discrete implementation based on standard graph search-based algorithms. We demonstrate the applicability of the proposed algorithm by solving efficient coverage problems on a sphere and a torus with obstacles, and exploration problems in non-convex indoor environments.

关键词： distributed robot systems mobile and distributed robotics slam path planning for multiple mobile robot systems autonomous agents cognitive robotics

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Aggressive flight of fixed-wing and quadrotor aircraft in dense indoor environments

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INTERNATIONAL JOURNAL OF robotics RESEARCH 2015年第7期34卷 969-1002页

作者： Bry, Adam Richter, Charles Bachrach, Abraham Roy, Nicholas MIT Comp Sci & Artificial Intelligence Lab Cambridge MA 02139 USA

In this paper, we describe trajectory planning and state estimation algorithms for aggressive flight of micro aerial vehicles in known, obstacle-dense environments. Finding aggressive but dynamically feasible and collision-free trajectories in cluttered environments requires trajectory optimization and state estimation in the full state space of the vehicle, which is usually computationally infeasible on realistic timescales for real vehicles and sensors. We first build on previous work of van Nieuwstadt and Murray and Mellinger and Kumar, to show how a search process can be coupled with optimization in the output space of a differentially flat vehicle model to find aggressive trajectories that utilize the full maneuvering capabilities of a quadrotor. We further extend this work to vehicles with complex, Dubins-type dynamics and present a novel trajectory representation called a Dubins-Polynomial trajectory, which allows us to optimize trajectories for fixed-wing vehicles. To provide accurate state estimation for aggressive flight, we show how the Gaussian particle filter can be extended to allow laser rangefinder localization to be combined with a Kalman filter. This formulation allows similar estimation accuracy to particle filtering in the full vehicle state but with an order of magnitude more efficiency. We conclude with experiments demonstrating the execution of quadrotor and fixed-wing trajectories in cluttered environments. We show results of aggressive flight at speeds of up to 8m/s for the quadrotor and 11m/s for the fixed-wing aircraft.

关键词： Non-holonomic motion planning mobile and distributed robotics slam localization sensor fusion sensing and perception computer vision aerial robotics field and service robotics motion control mechanics design and control

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Lifelong localization in changing environments

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INTERNATIONAL JOURNAL OF robotics RESEARCH 2013年第14期32卷 1662-1678页

作者： Tipaldi, Gian Diego Meyer-Delius, Daniel Burgard, Wolfram Univ Freiburg Dept Comp Sci D-79106 Freiburg Germany KUKA Labs GmbH Augsburg Germany

Robot localization systems typically assume that the environment is static, ignoring the dynamics inherent in most real-world settings. Corresponding scenarios include households, offices, warehouses and parking lots, where the location of certain objects such as goods, furniture or cars can change over time. These changes typically lead to inconsistent observations with respect to previously learned maps and thus decrease the localization accuracy or even prevent the robot from globally localizing itself. In this paper we present a sound probabilistic approach to lifelong localization in changing environments using a combination of a Rao-Blackwellized particle filter with a hidden Markov model. By exploiting several properties of this model, we obtain a highly efficient map management approach for dynamic environments, which makes it feasible to run our algorithm online. Extensive experiments with a real robot in a dynamically changing environment demonstrate that our algorithm reliably adapts to changes in the environment and also outperforms the popular Monte-Carlo localization approach.

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

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A bathymetric mapping and slam dataset with high-precision ground truth for marine robotics

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INTERNATIONAL JOURNAL OF robotics RESEARCH 2022年第1期41卷 12-19页

作者： Krasnosky, Kristopher Roman, Christopher Casagrande, David Univ Rhode Isl Grad Sch Oceanog Narragansett Bay Campus215 South Ferry Rd Narragansett RI 02882 USA

In recent years, sonar systems for surface and underwater vehicles have increased in resolution and become significantly less expensive. As such, these systems are viable at a wide range of price points and are appropriate for a broad set of applications on surface and underwater vehicles. However, to take full advantage of these high-resolution sensors for seafloor mapping tasks an adequate navigation solution is also required. In GPS-denied environments this usually necessitates a simultaneous localization and mapping (slam) technique to maintain good accuracy with minimal error accumulation. Acoustic positioning systems such as ultra short baseline (USBL) and long baseline (LBL) are sometimes deployed to provide additional bounds on the navigation solution, but the positional uncertainty of these systems is often much greater than the resolution of modern multibeam or interferometric side scan sonars. As such, subsurface vehicles often lack the means to adequately ground-truth navigation solutions and the resulting bathymetic maps. In this article, we present a dataset with four separate surveys designed to test bathymetric slam algorithms using two modern sonars, typical underwater vehicle navigation sensors, and high-precision (2 cm horizontal, 10 cm vertical) real-time kinematic (RTK) GPS ground truth. In addition, these data can be used to refine and improve other aspects of multibeam sonar mapping such as ray-tracing, gridding techniques, and time-varying attitude corrections.

关键词： mobile and distributed robotics slam Marine robotics Mapping Field Robots Localization Bathymetric

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Efficient data collection from wireless nodes under the two-ring communication model

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INTERNATIONAL JOURNAL OF robotics RESEARCH 2012年第6期31卷 774-784页

作者： Tekdas, Onur Bhadauria, Deepak Isler, Volkan Univ Minnesota Dept Comp Sci & Engn 200 Union St S E Minneapolis MN 55455 USA

We introduce a new geometric robot-routing problem which arises in data-muling applications where a mobile robot is charged with collecting data from stationary sensors. The objective is to compute the robot's trajectory and download sequence so as to minimize the time to collect data from all of the sensors. The total data collection time has two components: the robot's travel time and the download time. The time to download data from a sensor s is a function of the location of the robot and s: if the robot is a distance r(in) away from s, it can download the sensor's data in T-in units of time. If the distance is greater than r(in) but less than r(out), the download time is T-out > T-in. Otherwise, the robot can not download the data from s. Here, r(in), r(out), T-in and T-out are input parameters. We refer to this model, which is based on recently developed experimental models for sensor network deployments, as the two-ring model, and the problem of downloading data from a given set of sensors in minimum amount of time under this model as the two-ring tour (TRT) problem. We present approximation algorithms for the general case which uses solutions to the traveling salesperson with neighborhoods (TSPN) Problem as subroutines. We also present efficient solutions to special, but practically important versions of the problem such as grid-based and sparse deployments. The approach is validated in outdoor experiments.

关键词： Networked robots mobile and distributed robotics slam sensor networks sensing and perception computer vision robotics in agriculture and forestry field and service robotics

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The Malaga urban dataset: High-rate stereo and LiDAR in a realistic urban scenario

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INTERNATIONAL JOURNAL OF robotics RESEARCH 2014年第2期33卷 207-214页

作者： Blanco-Claraco, Jose-Luis Moreno-Duenas, Francisco-Angel Gonzalez-Jimenez, Javier Univ Almeria Dept Mech Engn La Canada De San Urbano 04120 Almeria Spain Univ Malaga Dept Syst Engn & Automat E-29071 Malaga Spain

This paper introduces a dataset gathered entirely in urban scenarios with a car equipped with one stereo camera and five laser scanners, among other sensors. One distinctive feature of the present dataset is the existence of high-resolution stereo images grabbed at a high rate (20 fps) during a 36.8 km trajectory, which allows the benchmarking of a variety of computer vision techniques. We describe the sensors employed and highlight some applications which could be benchmarked using the present work. Both plain text and binary files are provided, as well as open-source tools for working with the binary versions. The dataset is available for download at http://***/MalagaUrbanDataset.

关键词： recognition sensing and perception computer vision mobile and distributed robotics slam localization Mapping

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Ford Campus vision and lidar data set

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INTERNATIONAL JOURNAL OF robotics RESEARCH 2011年第13期30卷 1543-1552页

作者： Pandey, Gaurav McBride, James R. Eustice, Ryan M. Univ Michigan Dept Elect Engn & Comp Sci Ann Arbor MI 48105 USA Ford Motor Co Res Dearborn MI USA

In this paper we describe a data set collected by an autonomous ground vehicle testbed, based upon a modified Ford F-250 pickup truck. The vehicle is outfitted with a professional (Applanix POS-LV) and consumer (Xsens MTi-G) inertial measurement unit, a Velodyne three-dimensional lidar scanner, two push-broom forward-looking Riegl lidars, and a Point Grey Ladybug3 omnidirectional camera system. Here we present the time-registered data from these sensors mounted on the vehicle, collected while driving the vehicle around the Ford Research Campus and downtown Dearborn, MI, during November-December 2009. The vehicle path trajectory in these data sets contains several large-and small-scale loop closures, which should be useful for testing various state-of-the-art computer vision and simultaneous localization and mapping algorithms.

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

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Advanced perception, navigation and planning for autonomous in-water ship hull inspection

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INTERNATIONAL JOURNAL OF robotics RESEARCH 2012年第12期31卷 1445-1464页

作者： Hover, Franz S. Eustice, Ryan M. Kim, Ayoung Englot, Brendan Johannsson, Hordur Kaess, Michael Leonard, John J. MIT Cambridge MA 02139 USA Univ Michigan Ann Arbor MI 48109 USA

Inspection of ship hulls and marine structures using autonomous underwater vehicles has emerged as a unique and challenging application of robotics. The problem poses rich questions in physical design and operation, perception and navigation, and planning, driven by difficulties arising from the acoustic environment, poor water quality and the highly complex structures to be inspected. In this paper, we develop and apply algorithms for the central navigation and planning problems on ship hulls. These divide into two classes, suitable for the open, forward parts of a typical monohull, and for the complex areas around the shafting, propellers and rudders. On the open hull, we have integrated acoustic and visual mapping processes to achieve closed-loop control relative to features such as weld-lines and biofouling. In the complex area, we implemented new large-scale planning routines so as to achieve full imaging coverage of all the structures, at a high resolution. We demonstrate our approaches in recent operations on naval ships.

关键词： Marine robotics field and service robotics localization mobile and distributed robotics slam mapping sonars sensor fusion sensing and perception computer vision path planning for multiple mobile robot systems

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The Canadian planetary emulation terrain 3D mapping dataset

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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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Robust LIDAR localization using multiresolution Gaussian mixture maps for autonomous driving

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INTERNATIONAL JOURNAL OF robotics RESEARCH 2017年第3期36卷 292-319页

作者： Wolcott, Ryan W. Eustice, Ryan M. Univ Michigan Comp Sci & Engn Div Bldg 2600 Draper Dr Ann Arbor MI 48109 USA Ford Motor Co Dearborn MI 48121 USA Univ Michigan Dept Naval Architecture & Marine Engn Ann Arbor MI 48109 USA

This paper reports on a fast multiresolution scan matcher for local vehicle localization of self-driving cars. State-of-theart approaches to vehicle localization rely on observing road surface reflectivity with a 3D light detection and ranging (LIDAR) scanner to achieve centimeter-level accuracy. However, these approaches can often fail when faced with adverse weather conditions that obscure the view of the road paint (e.g. puddles and snowdrifts), poor road surface texture, or when road appearance degrades over time. We present a generic probabilistic method for localizing an autonomous vehicle equipped with a three-dimensional (3D) LIDAR scanner. This proposed algorithm models the world as a mixture of several Gaussians, characterizing the z-height and reflectivity distribution of the environment-which we rasterize to facilitate fast and exact multiresolution inference. Results are shown on a collection of datasets totaling over 500 km of road data covering highway, rural, residential, and urban roadways, in which we demonstrate our method to be robust through heavy snowfall and roadway repavements.

关键词： Field robots localization mapping mobile and distributed robotics slam

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