当前期刊: Journal of Field Robotics Go to current issue    加入关注    本刊投稿指南
显示样式:        排序: IF: - GO 导出
  • Fusion of neural networks, for LIDAR‐based evidential road mapping
    J. Field Robot. (IF 3.581) Pub Date : 2021-01-14
    Edouard Capellier; Franck Davoine; Véronique Cherfaoui; You Li

    LIDAR sensors are usually used to provide autonomous vehicles with three‐dimensional representations of their environment. In ideal conditions, geometrical models could detect the road in LIDAR scans, at the cost of a manual tuning of numerical constraints, and a lack of flexibility. We instead propose an evidential pipeline, to accumulate road detection results obtained from neural networks. First

  • Design, implementation, and verification of a low‐cost terminal guidance system for small fixed‐wing UAVs
    J. Field Robot. (IF 3.581) Pub Date : 2021-01-12
    Yachao Yang; Chang Liu; Jie Li; Yu Yang; Juan Li; Zhidong Zhang; Bobo Ye

    A terminal guidance control system for small fixed‐wing unmanned aerial vehicles (SUAV, with a wingspan of around 1.5 m) is proposed in this paper based on a visible light strap‐down seeker. The system is implemented using low‐cost, open‐source components with a cost less than $2000 and proved to be feasible, transplantable and effective for different types of SUAVs, achieving a good terminal guidance

  • Ocean front detection and tracking using a team of heterogeneous marine vehicles
    J. Field Robot. (IF 3.581) Pub Date : 2021-01-12
    Seth McCammon; Gilberto Marcon dos Santos; Matthew Frantz; T. P. Welch; Graeme Best; R. Kipp Shearman; Jonathan D. Nash; John A. Barth; Julie A. Adams; Geoffrey A. Hollinger

    Ocean monitoring is an expensive and time consuming endeavor, but it can be made more efficient through the use of teams of autonomous robots. In this paper, we present a system for the autonomous identification and tracking of ocean fronts by coordinating the sampling efforts of a heterogeneous team of autonomous surface vehicles (ASVs) and autonomous underwater vehicles (AUVs). The primary contributions

  • Low complexity visual UAV track navigation using long‐wavelength infrared
    J. Field Robot. (IF 3.581) Pub Date : 2021-01-11
    Kent Rosser; Tran Xuan Bach Nguyen; Philip Moss; Javaan Chahl

    Visual navigation is a commonly researched alternative to the use of global navigation satellite systems in challenging environments where satellite signals are not available. However, the vast majority of visual navigation techniques studied to date require scene illumination of some form. In this study, we use a low‐resolution long‐wave infrared (LWIR) image sensor sensitive to thermal emissivity

  • Mars curiosity rover mobility trends during the first 7 years
    J. Field Robot. (IF 3.581) Pub Date : 2021-01-09
    Arturo Rankin; Mark Maimone; Jeffrey Biesiadecki; Nikunj Patel; Dan Levine; Olivier Toupet

    NASA's Mars Science Laboratory (MSL) Curiosity rover landed on Mars on August 6, 2012. In the 7 years between landing and August 6, 2019 (sol 2488), Curiosity has driven 21,318.5 m over a variety of terrain types and slopes, employing multiple drive modes with varying amounts of onboard autonomy. Curiosity's drive distances each sol have ranged from its shortest drive of 2.6 cm to its longest drive

  • Cooperative acoustic navigation of underwater vehicles without a DVL utilizing a dynamic process model: Theory and field evaluation
    J. Field Robot. (IF 3.581) Pub Date : 2021-01-08
    Zachary J. Harris; Louis L. Whitcomb

    This paper reports the theoretical development and at‐sea field evaluation of a novel combined underwater acoustic communication and navigation system, known as cooperative acoustic navigation (CAN), for underwater vehicles (UVs) utilizing a second‐order dynamic plant model of the submerged UVs. The present state‐of‐the‐art in CAN is to utilize one‐way travel‐time acoustic modem telemetry together

  • Development and performance evaluation of a machine vision system and an integrated prototype for automated green shoot thinning in vineyards
    J. Field Robot. (IF 3.581) Pub Date : 2021-01-07
    Yaqoob Majeed; Manoj Karkee; Qin Zhang; Longsheng Fu; Matthew D. Whiting

    Green shoot thinning in vineyards is an essential, perennial operation for maintaining canopy health and optimizing yield and quality of wine grapes. Use of mechanized thinning system, which is essential to reduce labor dependency and associated cost, causes high variability in shoot removal efficiency due to difficulty in precisely positioning the thinning end‐effector along cordon trajectories. Automated/robotic

  • Canopy density estimation in perennial horticulture crops using 3D spinning lidar SLAM
    J. Field Robot. (IF 3.581) Pub Date : 2021-01-06
    Thomas Lowe; Peyman Moghadam; Everard Edwards; Jason Williams

    We propose a novel, canopy density estimation solution using a three‐dimensional (3D) ray cloud representation for perennial horticultural crops at the field scale. To attain high spatial and temporal fidelity in field conditions, we propose the application of continuous‐time 3D SLAM (simultaneous localization and mapping) to a spinning lidar payload (AgScan3D) mounted on a moving farm vehicle. The

  • An automated heterogeneous robotic system for radiation surveys: Design and field testing
    J. Field Robot. (IF 3.581) Pub Date : 2021-01-06
    Petr Gabrlik; Tomas Lazna; Tomas Jilek; Petr Sladek; Ludek Zalud

    During missions involving radiation exposure, unmanned robotic platforms may embody a valuable tool, especially thanks to their capability of replacing human operators in certain tasks to eliminate the health risks associated with such an environment. Moreover, rapid development of the technology allows us to increase the automation rate, making the human operator generally less important within the

  • Towards automating construction tasks: Large‐scale object mapping, segmentation, and manipulation
    J. Field Robot. (IF 3.581) Pub Date : 2020-12-22
    Ruben Mascaro; Martin Wermelinger; Marco Hutter; Margarita Chli

    Automating building processes through robotic systems has the potential to address the need for safer, more efficient, and sustainable construction operations. While ongoing research effort often targets the use of prefabricated materials in controlled environments, here we focus on utilizing objects found on‐site, such as irregularly shaped rocks and rubble, as a way of enabling novel types of construction

  • Adaptive sampling with an autonomous underwater vehicle in static marine environments
    J. Field Robot. (IF 3.581) Pub Date : 2020-12-16
    Paul Stankiewicz; Yew T. Tan; Marin Kobilarov

    This paper explores the use of autonomous underwater vehicles (AUVs) equipped with sensors to construct water quality models to aid in the assessment of important environmental hazards, for instance related to point‐source pollutants or localized hypoxic regions. Our focus is on problems requiring the autonomous discovery and dense sampling of critical areas of interest in real‐time, for which standard

  • Navigating high‐speed unmanned surface vehicles: System approach and validations
    J. Field Robot. (IF 3.581) Pub Date : 2020-12-09
    Jiayuan Zhuang; Lei Zhang; Bo Wang; Yumin Su; Hanbing Sun; Yuanchang Liu; Richard Bucknall

    With an increasing interest in the deployment of unmanned surface vehicles (USVs) to support complex ocean operations, high‐speed USVs (≥40 knots) have become an important option, especially in accomplishing demanding tasks such as coastal guarding. At present, there is a vast amount of studies focusing on the development of USVs' autonomous navigation systems, and the results of most of them have

  • Unmanned aircraft flight control aided by phased‐array radio navigation
    J. Field Robot. (IF 3.581) Pub Date : 2020-12-07
    Kristoffer Gryte; Torleiv H. Bryne; Tor A. Johansen

    Navigation systems of safety‐critical unmanned aircraft need an alternative position aiding source to global navigation satellite system. One promising alternative, is position measurements from phased‐array radio systems. The presented navigation system consist of a multiplicative extended Kalman filter that utilize these measurements, along with an exogenous altitude measurement, to aid an inertial

  • Radio propagation models for differential GNSS based on dense point clouds
    J. Field Robot. (IF 3.581) Pub Date : 2020-09-25
    Vladimír Kubelka; Philippe Dandurand; Philippe Babin; Philippe Giguère; François Pomerleau

    Accurate geolocation of mobile equipment operating in outdoor environments is an increasingly important question in robotics and automation. Modern geolocation systems, however, rely on the crucial ability for a mobile device to receive specific radio signals at all times. As such geolocation systems are increasingly deployed in harsh or difficult environments, for example, in the presence of tall

  • Graph‐based subterranean exploration path planning using aerial and legged robots
    J. Field Robot. (IF 3.581) Pub Date : 2020-11-01
    Tung Dang; Marco Tranzatto; Shehryar Khattak; Frank Mascarich; Kostas Alexis; Marco Hutter

    Autonomous exploration of subterranean environments remains a major challenge for robotic systems. In response, this paper contributes a novel graph‐based subterranean exploration path planning method that is attuned to key topological properties of subterranean settings, such as large‐scale tunnel‐like networks and complex multibranched topologies. Designed both for aerial and legged robots, the proposed

  • A real‐time quadrotor trajectory planning framework based on B‐spline and nonuniform kinodynamic search
    J. Field Robot. (IF 3.581) Pub Date : 2020-11-22
    Lvbang Tang; Hesheng Wang; Zhe Liu; Yong Wang

    Autonomous navigation of quadrotor is required by many application scenarios, such as exploration, search, and rescue. The trajectory planning algorithm is the core of autonomous navigation, which can undoubtedly greatly enhance the safety of flight. In this paper, a trajectory planning framework based on B‐spline and kinodynamic search is proposed. This framework can be used for a limited‐sensing

  • Automation and robotics in the cultivation of pome fruit: Where do we stand today?
    J. Field Robot. (IF 3.581) Pub Date : 2020-11-17
    Rafaël Verbiest; Kris Ruysen; Tanja Vanwalleghem; Eric Demeester; Karel Kellens

    The cultivation of apples and pears in orchards consists of several tasks that still demand much human labor. The cost of this skilled labor increases while the number of competent seasonal workers becomes insufficient. These facts are a threat to the fruit industry. To find a solution, this paper addresses current as well as future automation possibilities for the main orchard tasks as a profitable

  • Diver tracking in open waters: A low‐cost approach based on visual and acoustic sensor fusion
    J. Field Robot. (IF 3.581) Pub Date : 2020-11-17
    Walid Remmas; Ahmed Chemori; Maarja Kruusmaa

    The design of a robust perception method is a substantial component towards achieving underwater human–robot collaboration. However, in complex environments such as the oceans, perception is still a challenging issue. Data‐fusion of different sensing modalities can improve perception in dynamic and unstructured ocean environments. This study addresses the control of a highly maneuverable autonomous

  • Computer vision‐based tree trunk and branch identification and shaking points detection in Dense‐Foliage canopy for automated harvesting of apples
    J. Field Robot. (IF 3.581) Pub Date : 2020-11-09
    Xin Zhang; Manoj Karkee; Qin Zhang; Matthew D. Whiting

    Fresh market apples are one of the high‐value crops in the United States. Washington alone has produced two‐thirds of the annual national production in the past 10 years. However, the availability of seasonal labor is increasingly uncertain. Shake‐and‐catch automated harvesting solutions have, therefore, become attractive for addressing this challenge. One of the significant challenges in applying

  • Terrain‐aided navigation for long‐range AUVs in dynamic under‐mapped environments
    J. Field Robot. (IF 3.581) Pub Date : 2020-11-09
    Georgios Salavasidis; Andrea Munafò; Davide Fenucci; Catherine A. Harris; Thomas Prampart; Robert Templeton; Michael Smart; Daniel T. Roper; Miles Pebody; E. Povl Abrahamsen; Stephen D. McPhail; Eric Rogers; Alexander B. Phillips

    Deploying long‐range autonomous underwater vehicles (AUVs) mid‐water column in the deep ocean is one of the most challenging applications for these submersibles. Without external support and speed over the ground measurements, dead‐reckoning (DR) navigation inevitably experiences an error proportional to the mission range and the speed of the water currents. In response to this problem, a computationally

  • Localization for precision navigation in agricultural fields—Beyond crop row following
    J. Field Robot. (IF 3.581) Pub Date : 2020-11-09
    Wera Winterhalter; Freya Fleckenstein; Christian Dornhege; Wolfram Burgard

    The growing world population calls for more efficient and sustainable farming technologies. Automating agricultural tasks has great potential to improve farming technologies. A key requirement for full automation is the ability of agricultural vehicles to accurately navigate entire fields without damaging value crops. One important precondition for autonomous navigation is localization, that is, the

  • Underwater navigation with 2D forward looking SONAR: An adaptive unscented Kalman filter‐based strategy for AUVs
    J. Field Robot. (IF 3.581) Pub Date : 2020-10-23
    Matteo Franchi; Alessandro Ridolfi; Benedetto Allotta

    One of the most significant challenges in the underwater domain is to retrieve the autonomous underwater vehicle (AUV) position within the surrounding environment. Indeed, reliable navigation systems are fundamental to perform complex tasks and missions. Most of the navigation filters for AUVs are based on Bayesian estimators such as the linear Kalman Filter (KF), the extended KF, the unscented KF

  • A novel loop closure detection method with the combination of points and lines based on information entropy
    J. Field Robot. (IF 3.581) Pub Date : 2020-10-20
    Junyu Han; Ruifang Dong; Jiangming Kan

    Visual simultaneous localization and mapping (visual‐SLAM) is a prominent technology for autonomous navigation of mobile robots. As a significant requirement for visual‐SLAM, loop closure detection (LCD) involves recognizing a revisited place, thereby helping visual‐SLAM eliminate accumulated errors and obtain consistent maps. Conventional LCD approaches mainly rely on point features to detect the

  • Design and evaluation of a modular robotic plum harvesting system utilizing soft components
    J. Field Robot. (IF 3.581) Pub Date : 2020-09-25
    Jasper Brown; Salah Sukkarieh

    The human labor required for tree crop harvesting is a major cost component in fruit production and is increasing. To address this, many existing research works have sought to demonstrate commercially viable robotic harvesting for tree crops, though successful commercial products resulting from these have been few and far between. Systems developed for specific crops such as sweet peppers or apples

  • Autonomous boat driving system using sample‐efficient model predictive control‐based reinforcement learning approach
    J. Field Robot. (IF 3.581) Pub Date : 2020-09-25
    Yunduan Cui; Shigeki Osaki; Takamitsu Matsubara

    In this article, we propose a novel reinforcement learning (RL) approach specialized for autonomous boats: sample‐efficient probabilistic model predictive control (SPMPC), to iteratively learn control policies of boats in real ocean environments without human prior knowledge. SPMPC addresses difficulties arising from large uncertainties in this challenging application and the need for rapid adaptation

  • River segmentation for autonomous surface vehicle localization and river boundary mapping
    J. Field Robot. (IF 3.581) Pub Date : 2020-09-25
    Kevin Meier; Soon‐Jo Chung; Seth Hutchinson

    We present a vision‐based algorithm that identifies the boundary separating water from land in a river environment containing specular reflections. Our approach relies on the law of reflection. Assuming the surface of water behaves like a horizontal mirror, the border separating land from water corresponds to the border separating three‐dimensional (3D) data which are either above or below the surface

  • Object detection, recognition, and tracking from UAVs using a thermal camera
    J. Field Robot. (IF 3.581) Pub Date : 2020-09-24
    Frederik S. Leira; Håkon Hagen Helgesen; Tor Arne Johansen; Thor I. Fossen

    In this paper a multiple object detection, recognition, and tracking system for unmanned aerial vehicles (UAVs) has been studied. The system can be implemented on any UAVs platform, with the main requirement being that the UAV has a suitable onboard computational unit and a camera. It is intended to be used in a maritime object tracking system framework for UAVs, which enables a UAV to perform multiobject

  • WiMUST: A cooperative marine robotic system for autonomous geotechnical surveys
    J. Field Robot. (IF 3.581) Pub Date : 2020-09-16
    Enrico Simetti; Giovanni Indiveri; António M. Pascoal

    This paper presents the main results of the European H2020 WiMUST project, whose aim was the development of a system of cooperative autonomous underwater vehicles and autonomous surface vehicles for geotechnical surveying. In particular, insights on the overall robotic technologies and methodologies employed, ranging from the communications and navigation framework to the cooperative and coordinated

  • Autonomous platooning of multiple ground vehicles in rough terrain
    J. Field Robot. (IF 3.581) Pub Date : 2020-09-01
    Jongho Shin; Dong Jun Kwak; Jun Kim

    This study proposes an autonomous platooning algorithm, composed of velocity, and path planning systems, of multiple ground vehicles in rough terrain. The velocity planning system aims to maintain desired distance between preceding and rear vehicles, and the path planning system generates reliable path to make the vehicles move safely under the given rough environment. To supply a reliable velocity

  • Efficient obstacle detection based on prior estimation network and spatially constrained mixture model for unmanned surface vehicles
    J. Field Robot. (IF 3.581) Pub Date : 2020-08-25
    Jingyi Liu; Hengyu Li; Jun Luo; Shaorong Xie; Yu Sun

    Recently, spatially constrained mixture model has become the mainstream method for the task of vision‐based obstacle detection in unmanned surface vehicles (USVs), and has shown its potential of modeling the semantic structure of the marine environment. However, the expectation maximization (EM) optimization of this model is quite sensitive to initial values and easily falls into a local optimal solution

  • Efficient autonomous navigation for planetary rovers with limited resources
    J. Field Robot. (IF 3.581) Pub Date : 2020-08-25
    Levin Gerdes, Martin Azkarate, José Ricardo Sánchez‐Ibáñez, Luc Joudrier, Carlos Jesús Perez‐del‐Pulgar

    Rovers operating on Mars require more and more autonomous features to fulfill their challenging mission requirements. However, the inherent constraints of space systems render the implementation of complex algorithms an expensive and difficult task. In this paper, we propose an architecture for autonomous navigation. Efficient implementations of autonomous features are built on top of the ExoMars path

  • Experimental validation of the modeling and control of a multibody underwater vehicle manipulator system for sea mining exploration
    J. Field Robot. (IF 3.581) Pub Date : 2020-08-15
    Daniele Di Vito; Daniela De Palma; Enrico Simetti; Giovanni Indiveri; Gianluca Antonelli

    This paper presents the modeling approach and the control framework developed for the ROBUST EU Horizon 2020 project. The goal of this project is to showcase technologies and methodologies for future autonomous mineral exploration missions in deep‐sea sites with an Underwater Vehicle‐Manipulator System. Within the aim to make the system reliable in performing autonomously the entire mission, specific

  • Self‐reliant rovers for increased mission productivity
    J. Field Robot. (IF 3.581) Pub Date : 2020-08-11
    Daniel Gaines, Gary Doran, Michael Paton, Brandon Rothrock, Joseph Russino, Ryan Mackey, Robert Anderson, Raymond Francis, Chet Joswig, Heather Justice, Ksenia Kolcio, Gregg Rabideau, Steve Schaffer, Jacek Sawoniewicz, Ashwin Vasavada, Vincent Wong, Kathryn Yu, Ali‐akbar Agha‐mohammadi

    Achieving consistently high levels of productivity has been a challenge for Mars surface missions. While the rovers have made major discoveries and dramatically increased our understanding of Mars, they require a great deal of interaction from the operations teams, and achieving mission objectives can take longer than anticipated when productivity is paced by the ground teams' ability to react. We

  • Automatic three‐dimensional mapping for tree diameter measurements in inventory operations
    J. Field Robot. (IF 3.581) Pub Date : 2020-08-10
    Jean‐François Tremblay; Martin Béland; Richard Gagnon; François Pomerleau; Philippe Giguère

    Forestry is a major industry in many parts of the world, yet this potential domain of application area has been overlooked by the robotics community. For instance, forest inventory, a cornerstone of efficient and sustainable forestry, is still traditionally performed manually by qualified professionals. The lack of automation in this particular task, consisting chiefly of measuring tree attributes

  • AMZ Driverless: The full autonomous racing system
    J. Field Robot. (IF 3.581) Pub Date : 2020-08-04
    Juraj Kabzan, Miguel I. Valls, Victor J. F. Reijgwart, Hubertus F. C. Hendrikx, Claas Ehmke, Manish Prajapat, Andreas Bühler, Nikhil Gosala, Mehak Gupta, Ramya Sivanesan, Ankit Dhall, Eugenio Chisari, Napat Karnchanachari, Sonja Brits, Manuel Dangel, Inkyu Sa, Renaud Dubé, Abel Gawel, Mark Pfeiffer, Alexander Liniger, John Lygeros, Roland Siegwart

    This paper presents the algorithms and system architecture of an autonomous racecar. The introduced vehicle is powered by a software stack designed for robustness, reliability, and extensibility. To autonomously race around a previously unknown track, the proposed solution combines state of the art techniques from different fields of robotics. Specifically, perception, estimation, and control are incorporated

  • What localizes beneath: A metric multisensor localization and mapping system for autonomous underground mining vehicles
    J. Field Robot. (IF 3.581) Pub Date : 2020-08-01
    Adam Jacobson; Fan Zeng; David Smith; Nigel Boswell; Thierry Peynot; Michael Milford

    Robustly and accurately localizing vehicles in underground mines is particularly challenging due to the unavailability of GPS, variable and often poor lighting conditions, visual aliasing in long tunnels, and airborne dust and water. In this paper, we present a novel, infrastructure‐less, multisensor localization method for robust autonomous operation within underground mines. The proposed method integrates

  • The effect of data augmentation and network simplification on the image‐based detection of broccoli heads with Mask R‐CNN
    J. Field Robot. (IF 3.581) Pub Date : 2020-07-14
    Pieter M. Blok; Frits K. van Evert; Antonius P. M. Tielen; Eldert J. van Henten; Gert Kootstra

    In current practice, broccoli heads are selectively harvested by hand. The goal of our work is to develop a robot that can selectively harvest broccoli heads, thereby reducing labor costs. An essential element of such a robot is an image‐processing algorithm that can detect broccoli heads. In this study, we developed a deep learning algorithm for this purpose, using the Mask Region‐based Convolutional

  • Into the dirt: Datasets of sewer networks with aerial and ground platforms
    J. Field Robot. (IF 3.581) Pub Date : 2020-07-08
    David Alejo; François Chataigner; Daniel Serrano; Luis Merino; Fernando Caballero

    This paper presents an unprecedented set of data in a challenging underground environment: the visitable sewers of Barcelona. To the best of our knowledge, this is the first data set involving ground and aerial robots in such scenario: the sewer inspection autonomous robot (SIAR) ground robot and the autonomous robot for sewer inspection aerial platform. These platforms captured data from a great variety

  • Performance improvements of a sweet pepper harvesting robot in protected cropping environments
    J. Field Robot. (IF 3.581) Pub Date : 2020-06-21
    Chris Lehnert, Chris McCool, Inkyu Sa, Tristan Perez

    Using robots to harvest sweet peppers in protected cropping environments has remained unsolved despite considerable effort by the research community over several decades. In this paper, we present the robotic harvester, Harvey, designed for sweet peppers in protected cropping environments that achieved a 76.5% success rate on 68 fruit (within a modified scenario) which improves upon our prior work

  • Perceptive whole‐body planning for multilegged robots in confined spaces
    J. Field Robot. (IF 3.581) Pub Date : 2020-06-11
    Russell Buchanan; Lorenz Wellhausen; Marko Bjelonic; Tirthankar Bandyopadhyay; Navinda Kottege; Marco Hutter

    Legged robots are exceedingly versatile and have the potential to navigate complex, confined spaces due to their many degrees of freedom. As a result of the computational complexity, there exist no online planners for perceptive whole‐body locomotion of robots in tight spaces. In this paper, we present a new method for perceptive planning for multilegged robots, which generates body poses, footholds

  • Design, modeling, and control of an aerial manipulator for placement and retrieval of sensors in the environment
    J. Field Robot. (IF 3.581) Pub Date : 2020-06-01
    Salua Hamaza, Ioannis Georgilas, Guillermo Heredia, Aníbal Ollero, Thomas Richardson

    On‐site inspection of large‐scale infrastructure often involves high risks for the operators and high insurance costs. Despite several safety measures already in place to avoid accidents, an increasing concern has brought the need to remotely monitor hard‐to‐reach locations, for which the use of aerial robots able to interact with the environment has arisen. In this paper a novel approach to aerial

  • Controlling Ocean One: Human–robot collaboration for deep‐sea manipulation
    J. Field Robot. (IF 3.581) Pub Date : 2020-06-01
    Gerald Brantner; Oussama Khatib

    Deploying robots to explore venues that are inaccessible to humans, or simply inhospitable, has been a longstanding ambition of scientists, engineers, and explorers across numerous fields. The deep sea exemplifies an environment that is largely uncharted and denies human presence. Central to exploration is the capacity to deliver dexterous robotic manipulation to this unstructured environment. Unmanned

  • Learning features from georeferenced seafloor imagery with location guided autoencoders
    J. Field Robot. (IF 3.581) Pub Date : 2020-05-28
    Takaki Yamada; Adam Prügel‐Bennett; Blair Thornton

    Although modern machine learning has the potential to greatly speed up the interpretation of imagery, the varied nature of the seabed and limited availability of expert annotations form barriers to its widespread use in seafloor mapping applications. This motivates research into unsupervised methods that function without large databases of human annotations. This paper develops an unsupervised feature

  • Towards autonomous inspection of concrete deterioration in sewers with legged robots
    J. Field Robot. (IF 3.581) Pub Date : 2020-05-27
    Hendrik Kolvenbach; David Wisth; Russell Buchanan; Giorgio Valsecchi; Ruben Grandia; Maurice Fallon; Marco Hutter

    The regular inspection of sewer systems is essential to assess the level of degradation and to plan maintenance work. Currently, human inspectors must walk through sewers and use their sense of touch to inspect the roughness of the floor and check for cracks. The sense of touch is used since the floor is often covered by (waste) water and biofilm, which renders visual inspection very challenging. In

  • Autonomous navigation of MAVs in unknown cluttered environments
    J. Field Robot. (IF 3.581) Pub Date : 2020-05-23
    Leobardo Campos‐Macías; Rodrigo Aldana‐López; Rafael de la Guardia; José I. Parra‐Vilchis; David Gómez‐Gutiérrez

    Recently, there have been many advances in the algorithms required for autonomous navigation in unknown environments, such as mapping, collision avoidance, trajectory planning, and motion control. These components have been integrated into drones with high‐end computers and graphics processors. However, further development is required to enable compute‐constrained platforms with such autonomous navigation

  • Zeus: A system description of the two‐time winner of the collegiate SAE autodrive competition
    J. Field Robot. (IF 3.581) Pub Date : 2020-05-12
    Keenan Burnett; Jingxing Qian; Xintong Du; Linqiao Liu; David J. Yoon; Tianchang Shen; Susan Sun; Sepehr Samavi; Michael J. Sorocky; Mollie Bianchi; Kaicheng Zhang; Arkady Arkhangorodsky; Quinlan Sykora; Shichen Lu; Yizhou Huang; Angela P. Schoellig; Timothy D. Barfoot

    The SAE AutoDrive Challenge is a 3‐year collegiate competition to develop a self‐driving car by 2020. The second year of the competition was held in June 2019 at MCity, a mock town built for self‐driving car testing at the University of Michigan. Teams were required to autonomously navigate a series of intersections while handling pedestrians, traffic lights, and traffic signs. Zeus is aUToronto's

  • A marsupial robotic system for surveying and inspection of freshwater ecosystems
    J. Field Robot. (IF 3.581) Pub Date : 2020-05-10
    Michail Kalaitzakis; Brennan Cain; Nikolaos Vitzilaios; Ioannis Rekleitis; Jason Moulton

    Freshwater ecosystems are vast areas that are constantly changing and evolving. To maintain the ecosystem as well as the structures located close to bodies of water, frequent monitoring is required. Although dangerous and time consuming, manual operations are the conventional way of monitoring such areas. Recently, Autonomous Surface Vehicles (ASVs) have been proposed to undertake the monitoring task

  • Visual model‐predictive localization for computationally efficient autonomous racing of a 72‐g drone
    J. Field Robot. (IF 3.581) Pub Date : 2020-05-08
    Shuo Li, Erik van der Horst, Philipp Duernay, Christophe De Wagter, Guido C. H. E. de Croon

    Drone racing is becoming a popular e‐sport all over the world, and beating the best human drone race pilots has quickly become a new major challenge for artificial intelligence and robotics. In this paper, we propose a novel sensor fusion method called visual model‐predictive localization (VML). Within a small time window, VML approximates the error between the model prediction position and the visual

  • Magnetic survey and autonomous target reacquisition with a scalar magnetometer on a small AUV
    J. Field Robot. (IF 3.581) Pub Date : 2020-05-02
    Eric Gallimore, Eric Terrill, Andrew Pietruszka, Jeffrey Gee, Andrew Nager, Robert Hess

    A scalar magnetometer payload has been developed and integrated into a two‐man portable autonomous underwater vehicle (AUV) for geophysical and archeological surveys. The compact system collects data from a Geometrics microfabricated atomic magnetometer, a total‐field atomic magnetometer. Data from the sensor is both stored for post‐processing and made available to an onboard autonomy engine for real‐time

  • Multisensor online 3D view planning for autonomous underwater exploration
    J. Field Robot. (IF 3.581) Pub Date : 2020-05-02
    Eduard Vidal, Narcís Palomeras, Klemen Istenič, Nuno Gracias, Marc Carreras

    This study presents a novel octree‐based three‐dimensional (3D) exploration and coverage method for autonomous underwater vehicles (AUVs). Robotic exploration can be defined as the task of obtaining a full map of an unknown environment with a robotic system, achieving full coverage of the area of interest with data from a particular sensor or set of sensors. While most robotic exploration algorithms

  • Erratum
    J. Field Robot. (IF 3.581) Pub Date : 2020-04-24

    https://doi.org/10.1002/rob.21917 In Kaljaca, Vroegindeweij, and van Henten (2020), there is a change in the author group, name of one of the author, Angelo Mencarelli, was accidentally removed from the author list and needs to be added back. This article was published in Journal of Field Robotics in February 2020 (https://doi.org/10.1002/rob.21917). We apologize for the error. Updated author group

  • Falco: Fast likelihood‐based collision avoidance with extension to human‐guided navigation
    J. Field Robot. (IF 3.581) Pub Date : 2020-04-16
    Ji Zhang; Chen Hu; Rushat Gupta Chadha; Sanjiv Singh

    We propose a planning method to enable fast autonomous flight in cluttered environments. Typically, autonomous navigation through a complex environment requires a continuous search on a graph generated by a k‐connected grid or a probabilistic scheme. As the vehicle travels, updating the graph with data from onboard sensors is expensive as is the search on the graph especially if the paths must be kinodynamically

  • An open‐source system for vision‐based micro‐aerial vehicle mapping, planning, and flight in cluttered environments
    J. Field Robot. (IF 3.581) Pub Date : 2020-04-06
    Helen Oleynikova, Christian Lanegger, Zachary Taylor, Michael Pantic, Alexander Millane, Roland Siegwart, Juan Nieto

    We present an open‐source system for Micro‐Aerial Vehicle (MAV) autonomous navigation from vision‐based sensing. Our system focuses on dense mapping, safe local planning, and global trajectory generation, especially when using narrow field‐of‐view sensors in very cluttered environments. In addition, details about other necessary parts of the system and special considerations for applications in real‐world

  • ARDEA—An MAV with skills for future planetary missions
    J. Field Robot. (IF 3.581) Pub Date : 2020-03-12
    Philipp Lutz, Marcus G. Müller, Moritz Maier, Samantha Stoneman, Teodor Tomić, Ingo von Bargen, Martin J. Schuster, Florian Steidle, Armin Wedler, Wolfgang Stürzl, Rudolph Triebel

    We introduce a prototype flying platform for planetary exploration: autonomous robot design for extraterrestrial applications (ARDEA). Communication with unmanned missions beyond Earth orbit suffers from time delay, thus a key criterion for robotic exploration is a robot's ability to perform tasks without human intervention. For autonomous operation, all computations should be done on‐board and Global

  • SLAM for autonomous planetary rovers with global localization
    J. Field Robot. (IF 3.581) Pub Date : 2020-02-28
    Dimitrios Geromichalos, Martin Azkarate, Emmanouil Tsardoulias, Levin Gerdes, Loukas Petrou, Carlos Perez Del Pulgar

    This paper describes a novel approach to simultaneous localization and mapping (SLAM) techniques applied to the autonomous planetary rover exploration scenario to reduce both the relative and absolute localization errors, using two well‐proven techniques: particle filters and scan matching. Continuous relative localization is improved by matching high‐resolution sensor scans to the online created local

  • A 3D reactive collision avoidance algorithm for underactuated underwater vehicles
    J. Field Robot. (IF 3.581) Pub Date : 2020-02-28
    Martin S. Wiig, Kristin Y. Pettersen, Thomas R. Krogstad

    Avoiding collisions is an essential goal of the control system of autonomous vehicles. This paper presents a reactive algorithm for avoiding obstacles in a three‐dimensional space, and shows how the algorithm can be applied to an underactuated underwater vehicle. The algorithm is based on maintaining a constant avoidance angle to the obstacle, which ensures that a guaranteed minimum separation distance

  • Field observation of tornadic supercells by multiple autonomous fixed‐wing unmanned aircraft
    J. Field Robot. (IF 3.581) Pub Date : 2020-02-26
    Eric W. Frew, Brian Argrow, Steve Borenstein, Sara Swenson, C. Alexander Hirst, Henno Havenga, Adam Houston

    This paper presents the results of the design and field deployment of multiple autonomous fixed‐wing unmanned aircraft into supercell thunderstorms. As part of a field campaign in Spring 2019, up to three fixed‐wing unmanned aircraft were deployed simultaneously into different regions of supercell thunderstorms, To learn more about the atmospheric conditions that lead to the formation of tornadoes

  • Autonomous aerial robot using dual‐fisheye cameras
    J. Field Robot. (IF 3.581) Pub Date : 2020-02-25
    Wenliang Gao, Kaixuan Wang, Wenchao Ding, Fei Gao, Tong Qin, Shaojie Shen

    Safety is undoubtedly the most fundamental requirement for any aerial robotic application. It is essential to equip aerial robots with omnidirectional perception coverage to ensure safe navigation in complex environments. In this paper, we present a light‐weight and low‐cost omnidirectional perception system, which consists of two ultrawide field‐of‐view (FOV) fisheye cameras and a low‐cost inertial

  • High‐accuracy absolute positioning for the stationary planetary rover by integrating the star sensor and inclinometer
    J. Field Robot. (IF 3.581) Pub Date : 2020-02-18
    Yinhu Zhan, Yong Zheng, Chonghui Li, Ruopu Wang, Yongxing Zhu, Zhanglei Chen

    In this paper, we introduce a novel method for the high‐accuracy absolute position determination for planetary rovers using the star sensor and inclinometer. We describe the star sensor and inclinometer model and the alignment method for the two sensors. We deduce the compensation algorithm for the atmosphere refraction correction error in detail and provide the rover's position solution, which effectively

  • Field trials of an energy‐aware mission planner implemented on an autonomous surface vehicle
    J. Field Robot. (IF 3.581) Pub Date : 2020-02-11
    Fletcher Thompson, Roberto Galeazzi, Damien Guihen

    Mission planning for autonomous marine vehicles is nontrivial due to the dynamic and uncertain nature of the marine environment. Communication can be low‐bandwidth and is not always guaranteed, so the operator must rely on the vehicles to adjust their plans according to the realized state of the environment. This paper presents the improvements made to an energy‐aware mission planner that allows it

Contents have been reproduced by permission of the publishers.
Springer 纳米技术权威期刊征稿
ACS ES&T Engineering
ACS ES&T Water