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  • 1.
    Ahtiainen, Juhana
    et al.
    Department of Electrical Engineering and Automation, Aalto University, Espoo, Finland.
    Stoyanov, Todor
    Örebro University, School of Science and Technology.
    Saarinen, Jari
    GIM Ltd., Espoo, Finland.
    Normal Distributions Transform Traversability Maps: LIDAR-Only Approach for Traversability Mapping in Outdoor Environments2017In: Journal of Field Robotics, ISSN 1556-4959, E-ISSN 1556-4967, Vol. 34, no 3, 600-621 p.Article in journal (Refereed)
    Abstract [en]

    Safe and reliable autonomous navigation in unstructured environments remains a challenge for field robots. In particular, operating on vegetated terrain is problematic, because simple purely geometric traversability analysis methods typically classify dense foliage as nontraversable. As traversing through vegetated terrain is often possible and even preferable in some cases (e.g., to avoid executing longer paths), more complex multimodal traversability analysis methods are necessary. In this article, we propose a three-dimensional (3D) traversability mapping algorithm for outdoor environments, able to classify sparsely vegetated areas as traversable, without compromising accuracy on other terrain types. The proposed normal distributions transform traversability mapping (NDT-TM) representation exploits 3D LIDAR sensor data to incrementally expand normal distributions transform occupancy (NDT-OM) maps. In addition to geometrical information, we propose to augment the NDT-OM representation with statistical data of the permeability and reflectivity of each cell. Using these additional features, we train a support-vector machine classifier to discriminate between traversable and nondrivable areas of the NDT-TM maps. We evaluate classifier performance on a set of challenging outdoor environments and note improvements over previous purely geometrical traversability analysis approaches.

  • 2.
    Almqvist, Håkan
    et al.
    Örebro University, School of Science and Technology.
    Magnusson, Martin
    Örebro University, School of Science and Technology.
    Stoyanov, Todor
    Örebro University, School of Science and Technology.
    Lilienthal, Achim J.
    Örebro University, School of Science and Technology.
    Improving Point-Cloud Accuracy from a Moving Platform in Field Operations2013In: 2013 IEEE International Conference on Robotics and Automation (ICRA), IEEE conference proceedings, 2013, 733-738 p.Conference paper (Refereed)
    Abstract [en]

    This paper presents a method for improving the quality of distorted 3D point clouds made from a vehicle equipped with a laser scanner moving over uneven terrain. Existing methods that use 3D point-cloud data (for tasks such as mapping, localisation, and object detection) typically assume that each point cloud is accurate. For autonomous robots moving in rough terrain, it is often the case that the vehicle moves a substantial amount during the acquisition of one point cloud, in which case the data will be distorted. The method proposed in this paper is capable of increasing the accuracy of 3D point clouds, without assuming any specific features of the environment (such as planar walls), without resorting to a "stop-scan-go" approach, and without relying on specialised and expensive hardware. Each new point cloud is matched to the previous using normal-distribution-transform (NDT) registration, after which a mini-loop closure is performed with a local, per-scan, graph-based SLAM method. The proposed method increases the accuracy of both the measured platform trajectory and the point cloud. The method is validated on both real-world and simulated data.

  • 3.
    Andreasson, Henrik
    et al.
    Örebro University, School of Science and Technology.
    Bouguerra, Abdelbaki
    Örebro University, School of Science and Technology.
    Cirillo, Marcello
    Örebro University, School of Science and Technology.
    Dimitrov, Dimitar Nikolaev
    INRIA - Grenoble, Meylan, France .
    Driankov, Dimiter
    Örebro University, School of Science and Technology.
    Karlsson, Lars
    Örebro University, School of Science and Technology.
    Lilienthal, Achim J.
    Örebro University, School of Science and Technology.
    Pecora, Federico
    Örebro University, School of Science and Technology.
    Saarinen, Jari Pekka
    Örebro University, School of Science and Technology. Aalto University, Aalto, Finland .
    Sherikov, Aleksander
    Centre de recherche Grenoble, Rhône-Alpes, Grenoble, France .
    Stoyanov, Todor
    Örebro University, School of Science and Technology.
    Autonomous transport vehicles: where we are and what is missing2015In: IEEE robotics & automation magazine, ISSN 1070-9932, Vol. 22, no 1, 64-75 p.Article in journal (Refereed)
    Abstract [en]

    In this article, we address the problem of realizing a complete efficient system for automated management of fleets of autonomous ground vehicles in industrial sites. We elicit from current industrial practice and the scientific state of the art the key challenges related to autonomous transport vehicles in industrial environments and relate them to enabling techniques in perception, task allocation, motion planning, coordination, collision prediction, and control. We propose a modular approach based on least commitment, which integrates all modules through a uniform constraint-based paradigm. We describe an instantiation of this system and present a summary of the results, showing evidence of increased flexibility at the control level to adapt to contingencies.

  • 4.
    Andreasson, Henrik
    et al.
    Örebro University, School of Science and Technology.
    Saarinen, Jari
    Örebro University, School of Science and Technology.
    Cirillo, Marcello
    Örebro University, School of Science and Technology.
    Stoyanov, Todor
    Örebro University, School of Science and Technology.
    Lilienthal, Achim
    Örebro University, School of Science and Technology.
    Drive the Drive: From Discrete Motion Plans to Smooth Drivable Trajectories2014In: Robotics, E-ISSN 2218-6581, Vol. 3, no 4, 400-416 p.Article in journal (Refereed)
    Abstract [en]

    Autonomous navigation in real-world industrial environments is a challenging task in many respects. One of the key open challenges is fast planning and execution of trajectories to reach arbitrary target positions and orientations with high accuracy and precision, while taking into account non-holonomic vehicle constraints. In recent years, lattice-based motion planners have been successfully used to generate kinematically and kinodynamically feasible motions for non-holonomic vehicles. However, the discretized nature of these algorithms induces discontinuities in both state and control space of the obtained trajectories, resulting in a mismatch between the achieved and the target end pose of the vehicle. As endpose accuracy is critical for the successful loading and unloading of cargo in typical industrial applications, automatically planned paths have not been widely adopted in commercial AGV systems. The main contribution of this paper is a path smoothing approach, which builds on the output of a lattice-based motion planner to generate smooth drivable trajectories for non-holonomic industrial vehicles. The proposed approach is evaluated in several industrially relevant scenarios and found to be both fast (less than 2 s per vehicle trajectory) and accurate (end-point pose errors below 0.01 m in translation and 0.005 radians in orientation).

  • 5.
    Andreasson, Henrik
    et al.
    Örebro University, School of Science and Technology.
    Saarinen, Jari
    Örebro University, School of Science and Technology.
    Cirillo, Marcello
    Örebro University, School of Science and Technology. SCANIA AB, Södertälje, Sweden.
    Stoyanov, Todor
    Örebro University, School of Science and Technology.
    Lilienthal, Achim
    Örebro University, School of Science and Technology.
    Fast, continuous state path smoothing to improve navigation accuracy2015In: IEEE International Conference on Robotics and Automation (ICRA), 2015, IEEE Computer Society, 2015, 662-669 p.Conference paper (Refereed)
    Abstract [en]

    Autonomous navigation in real-world industrial environments is a challenging task in many respects. One of the key open challenges is fast planning and execution of trajectories to reach arbitrary target positions and orientations with high accuracy and precision, while taking into account non-holonomic vehicle constraints. In recent years, lattice-based motion planners have been successfully used to generate kinematically and kinodynamically feasible motions for non-holonomic vehicles. However, the discretized nature of these algorithms induces discontinuities in both state and control space of the obtained trajectories, resulting in a mismatch between the achieved and the target end pose of the vehicle. As endpose accuracy is critical for the successful loading and unloading of cargo in typical industrial applications, automatically planned paths have not be widely adopted in commercial AGV systems. The main contribution of this paper addresses this shortcoming by introducing a path smoothing approach, which builds on the output of a lattice-based motion planner to generate smooth drivable trajectories for non-holonomic industrial vehicles. In real world tests presented in this paper we demonstrate that the proposed approach is fast enough for online use (it computes trajectories faster than they can be driven) and highly accurate. In 100 repetitions we achieve mean end-point pose errors below 0.01 meters in translation and 0.002 radians in orientation. Even the maximum errors are very small: only 0.02 meters in translation and 0.008 radians in orientation.

  • 6.
    Andreasson, Henrik
    et al.
    Örebro University, School of Science and Technology.
    Stoyanov, Todor
    Örebro University, School of Science and Technology.
    Real time registration of RGB-D data using local visual features and 3D-NDT registration2012In: Proc. of International Conference on Robotics and Automation (ICRA) Workshop on Semantic Perception, Mapping and Exploration (SPME), IEEE, 2012Conference paper (Refereed)
    Abstract [en]

    Recent increased popularity of RGB-D capable sensors in robotics has resulted in a surge of related RGBD registration methods. This paper presents several RGB-D registration algorithms based on combinations between local visual feature and geometric registration. Fast and accurate transformation refinement is obtained by using a recently proposed geometric registration algorithm, based on the Three-Dimensional Normal Distributions Transform (3D-NDT). Results obtained on standard data sets have demonstrated mean translational errors on the order of 1 cm and rotational errors bellow 1 degree, at frame processing rates of about 15 Hz.

  • 7.
    Bennetts, Victor Hernandez
    et al.
    Örebro University, School of Science and Technology.
    Schaffernicht, Erik
    Örebro University, School of Science and Technology.
    Stoyanov, Todor
    Örebro University, School of Science and Technology.
    Lilienthal, Achim J.
    Örebro University, School of Science and Technology.
    Trincavelli, Marco
    Örebro University, School of Science and Technology.
    Robot Assisted Gas Tomography - Localizing Methane Leaks in Outdoor Environments2014In: 2014 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA), IEEE conference proceedings, 2014, 6362-6367 p.Conference paper (Refereed)
    Abstract [en]

    In this paper we present an inspection robot to produce gas distribution maps and localize gas sources in large outdoor environments. The robot is equipped with a 3D laser range finder and a remote gas sensor that returns integral concentration measurements. We apply principles of tomography to create a spatial gas distribution model from integral gas concentration measurements. The gas distribution algorithm is framed as a convex optimization problem and it models the mean distribution and the fluctuations of gases. This is important since gas dispersion is not an static phenomenon and furthermore, areas of high fluctuation can be correlated with the location of an emitting source. We use a compact surface representation created from the measurements of the 3D laser range finder with a state of the art mapping algorithm to get a very accurate localization and estimation of the path of the laser beams. In addition, a conic model for the beam of the remote gas sensor is introduced. We observe a substantial improvement in the gas source localization capabilities over previous state-of-the-art in our evaluation carried out in an open field environment.

  • 8. Birk, Andreas
    et al.
    Poppinga, Jann
    Stoyanov, Todor
    Örebro University, School of Science and Technology.
    Nevatia, Yashodhan
    Planetary Exploration in USARSim: A Case Study including Real World Data from Mars2009In: RoboCup 2008: Robot Soccer World Cup XII / [ed] Volume editors: Luca Iocchi, Hitoshi Matsubara, Alfredo Weitzenfeld, Changjiu Zhou, Springer Berlin Heidelberg , 2009, 463-472 p.Conference paper (Refereed)
    Abstract [en]

     Intelligent Mobile Robots are increasingly used in unstructured domains; one particularly challenging example for this is, planetary exploration. The preparation of according missions is highly non-trivial, especially as it is difficult to carry out realistic experiments without, very sophisticated infrastructures. In this paper, we argue that, the, Unified System for Automation and Robot Simulation (USARSim) offers interesting opportunities for research on planetary exploration by mobile robots. With the example of work on terrain classification, it, is shown how synthetic as well as real world data, from Mars call be used to test an algorithm's performance in USARSim. Concretely, experiments with an algorithm for the detection of negotiable ground oil a, planetary surface are presented. It is shown that the approach performs fast; and robust on planetary surfaces.

  • 9. Birk, Andreas
    et al.
    Stoyanov, Todor
    Örebro University, School of Science and Technology.
    Nevatia, Yashodhan
    Ambrus, Rares
    Poppinga, Jan
    Pathak, Kaustubh
    Terrain Classification for Autonomous Robot Mobility: from Safety, Security Rescue Robotics to Planetary Exploration2008Conference paper (Refereed)
  • 10.
    Canelhas, Daniel R.
    et al.
    Örebro University, School of Science and Technology.
    Stoyanov, Todor
    Örebro University, School of Science and Technology.
    Lilienthal, Achim J.
    Örebro University, School of Science and Technology.
    From Feature Detection in Truncated Signed Distance Fields to Sparse Stable Scene Graphs2016In: IEEE Robotics and Automation Letters, ISSN 2377-3766, Vol. 1, no 2, 1148-1155 p.Article in journal (Refereed)
    Abstract [en]

    With the increased availability of GPUs and multicore CPUs, volumetric map representations are an increasingly viable option for robotic applications. A particularly important representation is the truncated signed distance field (TSDF) that is at the core of recent advances in dense 3D mapping. However, there is relatively little literature exploring the characteristics of 3D feature detection in volumetric representations. In this paper we evaluate the performance of features extracted directly from a 3D TSDF representation. We compare the repeatability of Integral invariant features, specifically designed for volumetric images, to the 3D extensions of Harris and Shi & Tomasi corners. We also study the impact of different methods for obtaining gradients for their computation. We motivate our study with an example application for building sparse stable scene graphs, and present an efficient GPU-parallel algorithm to obtain the graphs, made possible by the combination of TSDF and 3D feature points. Our findings show that while the 3D extensions of 2D corner-detection perform as expected, integral invariants have shortcomings when applied to discrete TSDFs. We conclude with a discussion of the cause for these points of failure that sheds light on possible mitigation strategies.

  • 11.
    Canelhas, Daniel R.
    et al.
    Örebro University, School of Science and Technology.
    Stoyanov, Todor
    Örebro University, School of Science and Technology.
    Lilienthal, Achim J.
    Örebro University, School of Science and Technology.
    Improved local shape feature stability through dense model tracking2013In: Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), IEEE, 2013, 3203-3209 p.Conference paper (Refereed)
    Abstract [en]

    In this work we propose a method to effectively remove noise from depth images obtained with a commodity structured light sensor. The proposed approach fuses data into a consistent frame of reference over time, thus utilizing prior depth measurements and viewpoint information in the noise removal process. The effectiveness of the approach is compared to two state of the art, single-frame denoising methods in the context of feature descriptor matching and keypoint detection stability. To make more general statements about the effect of noise removal in these applications, we extend a method for evaluating local image gradient feature descriptors to the domain of 3D shape descriptors. We perform a comparative study of three classes of such descriptors: Normal Aligned Radial Features, Fast Point Feature Histograms and Depth Kernel Descriptors; and evaluate their performance on a real-world industrial application data set. We demonstrate that noise removal enabled by the dense map representation results in major improvements in matching across all classes of descriptors as well as having a substantial positive impact on keypoint detection reliability

  • 12.
    Canelhas, Daniel R.
    et al.
    Örebro University, School of Science and Technology.
    Stoyanov, Todor
    Örebro University, School of Science and Technology.
    Lilienthal, Achim J.
    Örebro University, School of Science and Technology.
    SDF tracker: a parallel algorithm for on-line pose estimation and scene reconstruction from depth images2013In: Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), IEEE, 2013, 3671-3676 p.Conference paper (Refereed)
    Abstract [en]

    Ego-motion estimation and environment mapping are two recurring problems in the field of robotics. In this work we propose a simple on-line method for tracking the pose of a depth camera in six degrees of freedom and simultaneously maintaining an updated 3D map, represented as a truncated signed distance function. The distance function representation implicitly encodes surfaces in 3D-space and is used directly to define a cost function for accurate registration of new data. The proposed algorithm is highly parallel and achieves good accuracy compared to state of the art methods. It is suitable for reconstructing single household items, workspace environments and small rooms at near real-time rates, making it practical for use on modern CPU hardware

  • 13. Carpin, Stefano
    et al.
    Stoyanov, Todor
    Örebro University, School of Science and Technology.
    Nevatia, Yashodhan
    Lewis, M.
    Wang, J.
    Quantitative Assessments of USARSim Accuracy2006Conference paper (Refereed)
  • 14.
    Charusta, Krzysztof
    et al.
    Örebro University, School of Science and Technology.
    Krug, Robert
    Örebro University, School of Science and Technology.
    Stoyanov, Todor
    Örebro University, School of Science and Technology.
    Dimitrov, Dimitar
    Örebro University, School of Science and Technology.
    Iliev, Boyko
    Örebro University, School of Science and Technology.
    Generation of independent contact regions on objects reconstructed from noisy real-world range data2012In: 2012 IEEE International Conference on Robotics and Automation (ICRA), IEEE conference proceedings, 2012, 1338-1344 p.Conference paper (Refereed)
    Abstract [en]

    The synthesis and evaluation of multi-fingered grasps on complex objects is a challenging problem that has received much attention in the robotics community. Although several promising approaches have been developed, applications to real-world systems are limited to simple objects or gripper configurations. The paradigm of Independent Contact Regions (ICRs) has been proposed as a way to increase the tolerance to grasp positioning errors. This concept is well established, though only on precise geometric object models. This work is concerned with the application of the ICR paradigm to models reconstructed from real-world range data. We propose a method for increasing the robustness of grasp synthesis on uncertain geometric models. The sensitivity of the ICR algorithm to noisy data is evaluated and a filtering approach is proposed to improve the quality of the final result.

  • 15.
    Ferri, Gabriele
    et al.
    Scuola Superiore Sant'Anna.
    Mondini, Alessio
    Scuola Superiore Sant'Anna.
    Manzi, Alessandro
    Scuola Superiore Sant'Anna.
    Mazzolai, Barbara
    Scuola Superiore Sant'Anna.
    Laschi, Cecilia
    Scuola Superiore Sant'Anna.
    Mattoli, Virgilio
    Scuola Superiore Sant'Anna.
    Reggente, Matteo
    Örebro University, School of Science and Technology.
    Stoyanov, Todor
    Örebro University, School of Science and Technology.
    Lilienthal, Achim J.
    Örebro University, School of Science and Technology.
    Lettere, Marco
    Scuola Superiore Sant'Anna.
    Dario, Paolo.
    Scuola Superiore Sant'Anna.
    DustCart, a Mobile Robot for Urban Environments: Experiments of Pollution Monitoring and Mapping during Autonomous Navigation in Urban Scenarios2010In: Proceedings of ICRA Workshop on Networked and Mobile Robot Olfaction in Natural, Dynamic Environments, 2010Conference paper (Refereed)
    Abstract [en]

    In the framework of DustBot European project, aimed at developing a new multi-robot system for urban hygiene management, we have developed a twowheeled robot: DustCart. DustCart aims at providing a solution to door-to-door garbage collection: the robot, called by a user, navigates autonomously to his/her house; collects the garbage from the user and discharges it in an apposite area. An additional feature of DustCart is the capability to monitor the air pollution by means of an on board Air Monitoring Module (AMM). The AMM integrates sensors to monitor several atmospheric pollutants, such as carbon monoxide (CO), particular matter (PM10), nitrogen dioxide (NO2), ozone (O3) plus temperature (T) and relative humidity (rHu). An Ambient Intelligence platform (AmI) manages the robots’ operations through a wireless connection. AmI is able to collect measurements taken by different robots and to process them to create a pollution distribution map. In this paper we describe the DustCart robot system, focusing on the AMM and on the process of creating the pollutant distribution maps. We report results of experiments of one DustCart robot moving in urban scenarios and producing gas distribution maps using the Kernel DM+V algorithm. These experiments can be considered as one of the first attempts to use robots as mobile monitoring devices that can complement the traditional fixed stations.

  • 16.
    Hernandez Bennetts, Victor
    et al.
    Örebro University, School of Science and Technology.
    Schaffernicht, Erik
    Örebro University, School of Science and Technology.
    Stoyanov, Todor
    Örebro University, School of Science and Technology.
    Lilienthal, Achim J.
    Örebro University, School of Science and Technology.
    Trincavelli, Marco
    Örebro University, School of Science and Technology.
    Robot assisted gas tomography: an alternative approach for the detection of fugitive methane emissions2014In: Workshop on Robot Monitoring, 2014Conference paper (Refereed)
    Abstract [en]

    Methane (CH4) based combustibles, such as Natural Gas (NG) and BioGas (BG), are considered bridge fuels towards a decarbonized global energy system. NG emits less CO2 during combustion than other fossil fuels and BG can be produced from organic waste. However, at BG production sites, leaks are common and CH4 can escape through fissures in pipes and insulation layers. While by regulation BG producers shall issue monthly CH4 emission reports, measurements are sparsely collected, only at a few predefined locations. Due to the high global warming potential of CH4, efficient leakage detection systems are critical. We present a robotics approach to localize CH4 leaks. In Robot assisted Gas Tomography (RGT), a mobile robot is equipped with remote gas sensors to create gas distribution maps, which can be used to infer the location of emitting sources. Spectroscopy based remote gas sensors report integral concentrations, which means that the measurements are spatially unresolved, with neither information regarding the gas distribution over the optical path nor the length of the s beam. Thus, RGT fuses different sensing modalities, such as range sensors for robot localization and ray tracing, in order to infer plausible gas distribution models that explain the acquired integral concentration measurements.

  • 17.
    Hernandez Bennetts, Victor
    et al.
    Örebro University, School of Science and Technology.
    Schaffernicht, Erik
    Örebro University, School of Science and Technology.
    Stoyanov, Todor
    Örebro University, School of Science and Technology.
    Lilienthal, Achim J.
    Örebro University, School of Science and Technology.
    Trincavelli, Marco
    Örebro University, School of Science and Technology.
    Robot assisted gas tomography: localizing methane leaks in outdoor environments2014In: Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), IEEE conference proceedings, 2014Conference paper (Refereed)
    Abstract [en]

    In this paper we present an inspection robot to produce gas distribution maps and localize gas sources in large outdoor environments. The robot is equipped with a 3D laser range finder and a remote gas sensor that returns integral concentration measurements. We apply principles of tomography to create a spatial gas distribution model from integral gas concentration measurements. The gas distribution algorithm is framed as a convex optimization problem and it models the mean distribution and the fluctuations of gases. This is important since gas dispersion is not an static phenomenon and furthermore, areas of high fluctuation can be correlated with the location of an emitting source. We use a compact surface representation created from the measurements of the 3D laser range finder with a state of the art mapping algorithm to get a very accurate localization and estimation of the path of the laser beams. In addition, a conic model for the beam of the remote gas sensor is introduced. We observe a substantial improvement in the gas source localization capabilities over previous state-of-the-art in our evaluation carried out in an open field environment.

  • 18.
    Krug, Robert
    et al.
    Örebro University, School of Science and Technology.
    Stoyanov, Todor
    Örebro University, School of Science and Technology.
    Bonilla, Manuel
    Interdepart. Research Center “E. Piaggio”; University of Pisa, Pisa, Italy.
    Tincani, Vinicio
    Interdepart. Research Center “E. Piaggio”; University of Pisa, Pisa, Italy.
    Vaskevicius, Narunas
    Interdepart. Research Center “E. Piaggio”; University of Pisa, Pisa, Italy.
    Fantoni, Gualtiero
    Interdepart. Research Center “E. Piaggio”; University of Pisa, Pisa, Italy.
    Birk, Andreas
    Interdepart. Research Center “E. Piaggio”; University of Pisa, Pisa, Italy.
    Lilienthal, Achim
    Örebro University, School of Science and Technology.
    Bicchi, Antonio
    Interdepart. Research Center “E. Piaggio”; University of Pisa, Pisa, Italy.
    Improving Grasp Robustness via In-Hand Manipulation with Active Surfaces2014In: Workshop on Autonomous Grasping and Manipulation: An Open Challenge, 2014Conference paper (Refereed)
  • 19.
    Krug, Robert
    et al.
    Örebro University, School of Science and Technology.
    Stoyanov, Todor
    Örebro University, School of Science and Technology.
    Bonilla, Manuel
    Interdepart. Research Center “E. Piaggio”, University of Pisa, Pisa, Italy.
    Tincani, Vinicio
    Interdepart. Research Center “E. Piaggio”, University of Pisa, Pisa, Italy.
    Vaskevicius, Narunas
    Robotics Group, School of Engineering and Science, Jacobs University Bremen, Bremen, Germany.
    Fantoni, Gualtiero
    Interdepart. Research Center “E. Piaggio”, University of Pisa, Pisa, Italy.
    Birk, Andreas
    Robotics Group, School of Engineering and Science, Jacobs University Bremen, Bremen, Germany.
    Lilienthal, Achim J.
    Örebro University, School of Science and Technology.
    Bicchi, Antonio
    Interdepart. Research Center “E. Piaggio”, University of Pisa, Pisa, Italy.
    Velvet fingers: grasp planning and execution for an underactuated gripper with active surfaces2014In: Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), IEEE conference proceedings, 2014, 3669-3675 p.Conference paper (Refereed)
    Abstract [en]

    In this work we tackle the problem of planning grasps for an underactuated gripper which enable it to retrieve target objects from a cluttered environment. Furthermore,we investigate how additional manipulation capabilities of the gripping device, provided by active surfaces on the inside of the fingers, can lead to performance improvement in the grasp execution process. To this end, we employ a simple strategy, in which the target object is ‘pulled-in’ towards the palm during grasping which results in firm enveloping grasps. We show the effectiveness of the suggested methods by means of experiments conducted in a real-world scenario.

  • 20.
    Krug, Robert
    et al.
    Örebro University, School of Science and Technology.
    Stoyanov, Todor
    Örebro University, School of Science and Technology.
    Lilienthal, Achim
    Örebro University, School of Science and Technology.
    Grasp Envelopes for Constraint-based Robot Motion Planning and Control2015In: Robotics: Science and Systems Conference: Workshop on Bridging the Gap between Data-driven and Analytical Physics-based Grasping and Manipulation, 2015Conference paper (Refereed)
    Abstract [en]

    We suggest a grasp represen-tation in form of a set of enveloping spatial constraints. Our representation transforms the grasp synthesisproblem (i. e., the question of where to position the graspingdevice) from finding a suitable discrete manipulator wrist pose to finding a suitable pose manifold. Also the correspondingmotion planning and execution problem is relaxed – insteadof transitioning the wrist to a discrete pose, it is enough tomove it anywhere within the grasp envelope which allows toexploit kinematic redundancy.

  • 21.
    Krug, Robert
    et al.
    Örebro University, School of Science and Technology.
    Stoyanov, Todor
    Örebro University, School of Science and Technology.
    Tincani, Vinicio
    Interdepart. Research Center “E. Piaggio”; University of Pisa, Pisa, Italy.
    Andreasson, Henrik
    Örebro University, School of Science and Technology.
    Mosberger, Rafael
    Örebro University, School of Science and Technology.
    Fantoni, Gualtiero
    Interdepart. Research Center “E. Piaggio”; University of Pisa, Pisa, Italy.
    Bicchi, Antonio
    Interdepart. Research Center “E. Piaggio”; University of Pisa, Pisa, Italy.
    Lilienthal, Achim
    Örebro University, School of Science and Technology.
    On Using Optimization-based Control instead of Path-Planning for Robot Grasp Motion Generation2015In: IEEE International Conference on Robotics and Automation (ICRA) - Workshop on Robotic Hands, Grasping, and Manipulation, 2015Conference paper (Refereed)
  • 22.
    Krug, Robert
    et al.
    Örebro University, School of Science and Technology.
    Stoyanov, Todor
    Örebro University, School of Science and Technology.
    Tincani, Vinicio
    University of Pisa, Pisa, Italy.
    Andreasson, Henrik
    Örebro University, School of Science and Technology.
    Mosberger, Rafael
    Örebro University, School of Science and Technology.
    Fantoni, Gualtiero
    University of Pisa, Pisa, Italy.
    Lilienthal, Achim J.
    Örebro University, School of Science and Technology.
    The Next Step in Robot Commissioning: Autonomous Picking and Palletizing2016In: IEEE Robotics and Automation Letters, ISSN 2377-3766, Vol. 1, no 1, 546-553 p.Article in journal (Refereed)
    Abstract [en]

    So far, autonomous order picking (commissioning) systems have not been able to meet the stringent demands regarding speed, safety, and accuracy of real-world warehouse automation, resulting in reliance on human workers. In this letter, we target the next step in autonomous robot commissioning: automatizing the currently manual order picking procedure. To this end, we investigate the use case of autonomous picking and palletizing with a dedicated research platform and discuss lessons learned during testing in simplified warehouse settings. The main theoretical contribution is a novel grasp representation scheme which allows for redundancy in the gripper pose placement. This redundancy is exploited by a local, prioritized kinematic controller which generates reactive manipulator motions on-the-fly. We validated our grasping approach by means of a large set of experiments, which yielded an average grasp acquisition time of 23.5 s at a success rate of 94.7%. Our system is able to autonomously carry out simple order picking tasks in a humansafe manner, and as such serves as an initial step toward future commercial-scale in-house logistics automation solutions.

  • 23.
    Magnusson, Martin
    et al.
    Örebro University, School of Science and Technology.
    Vaskevicius, Narunas
    Deptartment of EECS, Jacobs University, Bremen, Germany.
    Stoyanov, Todor
    Örebro University, School of Science and Technology.
    Pathak, Kaustubh
    Deptartment of EECS, Jacobs University, Bremen, Germany.
    Birk, Andreas
    Deptartment of EECS, Jacobs University, Bremen, Germany.
    Beyond points: Evaluating recent 3D scan-matching algorithms2015In: 2015 IEEE International Conference on Robotics and Automation (ICRA), IEEE conference proceedings , 2015, Vol. 2015 June, 3631-3637 p.Conference paper (Refereed)
    Abstract [en]

    Given that 3D scan matching is such a central part of the perception pipeline for robots, thorough and large-scale investigations of scan matching performance are still surprisingly few. A crucial part of the scientific method is to perform experiments that can be replicated by other researchers in order to compare different results. In light of this fact, this paper presents a thorough comparison of 3D scan registration algorithms using a recently published benchmark protocol which makes use of a publicly available challenging data set that covers a wide range of environments. In particular, we evaluate two types of recent 3D registration algorithms - one local and one global. Both approaches take local surface structure into account, rather than matching individual points. After well over 100 000 individual tests, we conclude that algorithms using the normal distributions transform (NDT) provides accurate results compared to a modern implementation of the iterative closest point (ICP) method, when faced with scan data that has little overlap and weak geometric structure. We also demonstrate that the minimally uncertain maximum consensus (MUMC) algorithm provides accurate results in structured environments without needing an initial guess, and that it provides useful measures to detect whether it has succeeded or not. We also propose two amendments to the experimental protocol, in order to provide more valuable results in future implementations.

  • 24.
    Mojtahedzadeh, Rasoul
    et al.
    Örebro University, School of Science and Technology. Univ Örebro, Ctr Appl Autonomous Sensor Syst AASS, Örebro, Sweden.
    Stoyanov, Todor
    Örebro University, School of Science and Technology. Univ Örebro, Ctr Appl Autonomous Sensor Syst AASS, Örebro, Sweden.
    Lilienthal, Achim J.
    Örebro University, School of Science and Technology. Univ Örebro, Ctr Appl Autonomous Sensor Syst AASS, Örebro, Sweden.
    Application Based 3D Sensor Evaluation: A Case Study in 3D Object Pose Estimation for Automated Unloading of Containers2013In: Proceedings of the European Conference on Mobile Robots (ECMR), IEEE conference proceedings, 2013, 313-318 p.Conference paper (Other academic)
    Abstract [en]

    A fundamental task in the design process of a complex system that requires 3D visual perception is the choice of suitable 3D range sensors. Identifying the utility of 3D range sensors in an industrial application solely based on an evaluation of their distance accuracy and the noise level may lead to an inappropriate selection. To assess the actual effect on the performance of the system as a whole requires a more involved analysis. In this paper, we examine the problem of selecting a set of 3D range sensors when designing autonomous systems for specific industrial applications in a holistic manner. As an instance of this problem we present a case study with an experimental evaluation of the utility of four 3D range sensors for object pose estimation in the process of automation of unloading containers.

  • 25.
    Nevatia, Yashodhan
    et al.
    Univ Bremen, Dept EECS, Robot Lab, D-28725 Bremen, Germany.
    Stoyanov, Todor
    Örebro University, School of Science and Technology.
    Rathnam, Ravi
    Univ Bremen, Dept EECS, Robot Lab, D-28725 Bremen, Germany.
    Pfingsthorn, Max
    Markov, Stefan
    Ambrus, Rares
    Birk, Andreas
    Augmented Autonomy: Improving human-robot team performance in Urban Search and Rescue2008In: 2008 IEEE/RSJ International Conference on Robots and Intelligent Systems, vols 1-3, conference proceedings, New York: IEEE Robotics and Automation Society, 2008, 2103-2108 p.Conference paper (Refereed)
    Abstract [en]

    Exploration of unknown environments remains one of the fundamental problems of mobile robotics. It is also a prime example for a task that can benefit significantly from multi-robot teams. We present an integrated system for semi-autonomous cooperative exploration, augmented by an intuitive user interface for efficient human supervision and control. In this preliminary study we demonstrate the effectiveness of the system as a whole and the intuitive interface in particular. Congruent with previous findings, results confirm that having a human in the loop improves task performance, especially with larger numbers of robots. Specific to our interface, we find that even untrained operators can efficiently manage a decently sized team of robots.

  • 26.
    Pfingsthorn, Max
    et al.
    Jacobs University Bremen, Campus Ring 1, 28759 Bremen, Germany.
    Nevatia, Yashodhan
    Jacobs University Bremen, Campus Ring 1, 28759 Bremen, Germany.
    Stoyanov, Todor
    Örebro University, School of Science and Technology.
    Rathnam, Ravi
    Jacobs University Bremen, Campus Ring 1, 28759 Bremen, Germany.
    Markov, Stefan
    Jacobs University Bremen, Campus Ring 1, 28759 Bremen, Germany.
    Birk, Andreas
    Jacobs University Bremen, Campus Ring 1, 28759 Bremen, Germany.
    Towards Cooperative and Decentralized Mapping in the Jacobs Virtual Rescue Team2009In: RoboCup 2008: Robot Soccer World Cup XII Vol 5399 / [ed] Iocchi, Luca; Matsubara, Hitoshi; Weitzenfeld, Alfredo; Zhou, Changjiu, Springer Berlin / Heidelberg , 2009, Vol. 5399, 225-234 p.Chapter in book (Other academic)
    Abstract [en]

    The task of mapping and exploring an unknown environment remains one of the fundamental problems of mobile robotics. It is a task that can intuitively benefit significantly from a multi-robot approach. In this paper, we describe the design of the multi-robot mapping system used in the Jacobs Virtual Rescue team. The team competed in the World Cup 2007 and won the second place. It is shown how the recently proposed pose graph map representation facilitates not only map merging but also allows transmitting map updates efficiently

  • 27.
    Saarinen, Jari
    et al.
    Örebro University, School of Science and Technology.
    Andreasson, Henrik
    Örebro University, School of Science and Technology.
    Stoyanov, Todor
    Örebro University, School of Science and Technology.
    Ala-Luhtala, Juha
    Aalto University of Technology.
    Lilienthal, Achim J.
    Örebro University, School of Science and Technology.
    Normal distributions transform occupancy maps: application to large-scale online 3D mapping2013In: IEEE International Conference on Robotics and Automation, New York: IEEE conference proceedings, 2013, 2233-2238 p.Conference paper (Refereed)
    Abstract [en]

    Autonomous vehicles operating in real-world industrial environments have to overcome numerous challenges, chief among which is the creation and maintenance of consistent 3D world models. This paper proposes to address the challenges of online real-world mapping by building upon previous work on compact spatial representation and formulating a novel 3D mapping approach — the Normal Distributions Transform Occupancy Map (NDT-OM). The presented algorithm enables accurate real-time 3D mapping in large-scale dynamic nvironments employing a recursive update strategy. In addition, the proposed approach can seamlessly provide maps at multiple resolutions allowing for fast utilization in high-level functions such as localization or path planning. Compared to previous approaches that use the NDT representation, the proposed NDT-OM formulates an exact and efficient recursive update formulation and models the full occupancy of the map.

  • 28.
    Saarinen, Jari
    et al.
    Örebro University, School of Science and Technology.
    Andreasson, Henrik
    Örebro University, School of Science and Technology.
    Stoyanov, Todor
    Örebro University, School of Science and Technology.
    Lilienthal, Achim J.
    Örebro University, School of Science and Technology.
    3D normal distributions transform occupancy maps: an efficient representation for mapping in dynamic environments2013In: The international journal of robotics research, ISSN 0278-3649, E-ISSN 1741-3176, Vol. 32, no 14, 1627-1644 p.Article in journal (Refereed)
    Abstract [en]

    In order to enable long-term operation of autonomous vehicles in industrial environments numerous challenges need to be addressed. A basic requirement for many applications is the creation and maintenance of consistent 3D world models. This article proposes a novel 3D spatial representation for online real-world mapping, building upon two known representations: normal distributions transform (NDT) maps and occupancy grid maps. The proposed normal distributions transform occupancy map (NDT-OM) combines the advantages of both representations; compactness of NDT maps and robustness of occupancy maps. One key contribution in this article is that we formulate an exact recursive updates for NDT-OMs. We show that the recursive update equations provide natural support for multi-resolution maps. Next, we describe a modification of the recursive update equations that allows adaptation in dynamic environments. As a second key contribution we introduce NDT-OMs and formulate the occupancy update equations that allow to build consistent maps in dynamic environments. The update of the occupancy values are based on an efficient probabilistic sensor model that is specially formulated for NDT-OMs. In several experiments with a total of 17 hours of data from a milk factory we demonstrate that NDT-OMs enable real-time performance in large-scale, long-term industrial setups.

  • 29.
    Saarinen, Jari
    et al.
    Örebro University, School of Science and Technology.
    Andreasson, Henrik
    Örebro University, School of Science and Technology.
    Stoyanov, Todor
    Örebro University, School of Science and Technology.
    Lilienthal, Achim J.
    Örebro University, School of Science and Technology.
    Normal distributions transform monte-carlo localization (NDT-MCL)2013In: Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), IEEE, 2013, 382-389 p.Conference paper (Refereed)
  • 30.
    Saarinen, Jari
    et al.
    Örebro University, School of Science and Technology.
    Stoyanov, Todor
    Örebro University, School of Science and Technology.
    Andreasson, Henrik
    Örebro University, School of Science and Technology.
    Lilienthal, Achim J.
    Örebro University, School of Science and Technology.
    Fast 3D mapping in highly dynamic environments using normal distributions transform occupancy maps2013In: Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), IEEE, 2013, 4694-4701 p.Conference paper (Refereed)
  • 31.
    Stoyanov, Todor Dimitrov
    Örebro University, School of Science and Technology.
    Reliable autonomus navigation in semi-structured environments using the three-dimensional normal distributions transform (3D-NDT)2012Doctoral thesis, comprehensive summary (Other academic)
  • 32.
    Stoyanov, Todor
    et al.
    Örebro University, School of Science and Technology.
    Krug, Robert
    Örebro University, School of Science and Technology.
    Muthusamy, Rajkumar
    Aalto University, Aalto, Finland.
    Kyrki, Ville
    Aalto University, Aalto, Finland.
    Grasp Envelopes: Extracting Constraints on Gripper Postures from Online Reconstructed 3D Models2016In: Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), New York: Institute of Electrical and Electronics Engineers (IEEE), 2016, 885-892 p.Conference paper (Refereed)
    Abstract [en]

    Grasping systems that build upon meticulously planned hand postures rely on precise knowledge of object geometry, mass and frictional properties - assumptions which are often violated in practice. In this work, we propose an alternative solution to the problem of grasp acquisition in simple autonomous pick and place scenarios, by utilizing the concept of grasp envelopes: sets of constraints on gripper postures. We propose a fast method for extracting grasp envelopes for objects that fit within a known shape category, placed in an unknown environment. Our approach is based on grasp envelope primitives, which encode knowledge of human grasping strategies. We use environment models, reconstructed from noisy sensor observations, to refine the grasp envelope primitives and extract bounded envelopes of collision-free gripper postures. Also, we evaluate the envelope extraction procedure both in a stand alone fashion, as well as an integrated component of an autonomous picking system.

  • 33.
    Stoyanov, Todor
    et al.
    Örebro University, School of Science and Technology.
    Lilienthal, Achim J.
    Örebro University, School of Science and Technology.
    Maximum Likelihood Point Cloud Acquisition from a Rotating Laser Scanner on a Moving Platform2009In: Proceedings of the IEEE International Conference on Advanced Robotics (ICAR), IEEE conference proceedings, 2009Conference paper (Refereed)
    Abstract [en]

    This paper describes an approach to acquire locally consistent range data scans from a moving sensor platform. Data from a vertically mounted rotating laser scanner and odometry position estimates are fused and used to estimate maximum likelihood point clouds. An estimation algorithm is applied to reduce the accumulated error after a full rotation of the range finder. A configuration consisting of a SICK laser scanner mounted on a rotational actuator is described and used to evaluate the proposed approach. The data sets analyzed suggest a significant improvement in point cloud consistency, even over a short travel distance.

  • 34.
    Stoyanov, Todor
    et al.
    Örebro University, School of Science and Technology.
    Lilienthal, Achim J.
    Örebro University, School of Science and Technology.
    Maximum likelihood point cloud acquisition from a mobile platform2009In: International conference on advanced robotics, ICAR 2009., New York: IEEE conference proceedings, 2009, 1-6 p.Conference paper (Refereed)
    Abstract [en]

    This paper describes an approach to acquire locally consistent range data scans from a moving sensor platform. Data from a vertically mounted rotating laser scanner and odometry position estimates are fused and used to estimate maximum likelihood point clouds. An estimation algorithm is applied to reduce the accumulated error after a full rotation of the range finder. A configuration consisting of a SICK laser scanner mounted on a rotational actuator is described and used to evaluate the proposed approach. The data sets analyzed suggest a significant improvement in point cloud consistency, even over a short travel distance.

  • 35.
    Stoyanov, Todor
    et al.
    Örebro University, School of Science and Technology.
    Louloudi, Athanasia
    Örebro University, School of Science and Technology.
    Andreasson, Henrik
    Örebro University, School of Science and Technology.
    Lilienthal, Achim J.
    Örebro University, School of Science and Technology.
    Comparative evaluation of range sensor accuracy in indoor environments2011In: Proceedings of the 5th European Conference on Mobile Robots, ECMR 2011 / [ed] Achim J. Lilienthal, Tom Duckett, 2011, 19-24 p.Conference paper (Refereed)
    Abstract [en]

    3D range sensing is one of the important topics in robotics, as it is often a component in vital autonomous subsystems like collision avoidance, mapping and semantic perception. The development of affordable, high frame rate and precise 3D range sensors is thus of considerable interest. Recent advances in sensing technology have produced several novel sensors that attempt to meet these requirements. This work is concerned with the development of a holistic method for accuracy evaluation of the measurements produced by such devices. A method for comparison of range sensor output to a set of reference distance measurements is proposed. The approach is then used to compare the behavior of three integrated range sensing devices, to that of a standard actuated laser range sensor. Test cases in an uncontrolled indoor environment are performed in order to evaluate the sensors’ performance in a challenging, realistic application scenario.

  • 36.
    Stoyanov, Todor
    et al.
    Örebro University, School of Science and Technology.
    Magnusson, Martin
    Örebro University, School of Science and Technology.
    Almqvist, Håkan
    Örebro University, School of Science and Technology.
    Lilienthal, Achim J.
    Örebro University, School of Science and Technology.
    On the Accuracy of the 3D Normal Distributions Transform as a Tool for Spatial Representation2011In: 2011 IEEE International Conference on Robotics and Automation (ICRA), IEEE conference proceedings, 2011Conference paper (Refereed)
    Abstract [en]

    The Three-Dimensional Normal Distributions Transform (3D-NDT) is a spatial modeling technique with applications in point set registration, scan similarity comparison, change detection and path planning. This work concentrates on evaluating three common variations of the 3D-NDT in terms of accuracy of representing sampled semi-structured environments. In a novel approach to spatial representation quality measurement, the 3D geometrical modeling task is formulated as a classification problem and its accuracy is evaluated with standard machine learning performance metrics. In this manner the accuracy of the 3D-NDT variations is shown to be comparable to, and in some cases to outperform that of the standard occupancy grid mapping model.

  • 37.
    Stoyanov, Todor
    et al.
    Örebro University, School of Science and Technology.
    Magnusson, Martin
    Örebro University, School of Science and Technology.
    Andreasson, Henrik
    Örebro University, School of Science and Technology.
    Lilienthal, Achim J.
    Örebro University, School of Science and Technology.
    Path planning in 3D environments using the normal distributions transform2010In: IEEE/RSJ 2010 International Conference on Intelligent Robots and Systems (IROS 2010), IEEE conference proceedings, 2010, 3263-3268 p.Conference paper (Other academic)
    Abstract [en]

    Planning feasible paths in fully three-dimensional environments is a challenging problem. Application of existing algorithms typically requires the use of limited 3D representations that discard potentially useful information. This article proposes a novel approach to path planning that utilizes a full 3D representation directly: the Three-Dimensional Normal Distributions Transform (3D-NDT). The well known wavefront planner is modified to use 3D-NDT as a basis for map representation and evaluated using both indoor and outdoor data sets. The use of 3D-NDT for path planning is thus demonstrated to be a viable choice with good expressive capabilities.

  • 38.
    Stoyanov, Todor
    et al.
    Örebro University, School of Science and Technology.
    Magnusson, Martin
    Örebro University, School of Science and Technology.
    Lilienthal, Achim J.
    Örebro University, School of Science and Technology.
    Comparative evaluation of the consistency of three-dimensional spatial representations used in autonomous robot navigation2013In: Journal of Field Robotics, ISSN 1556-4959, E-ISSN 1556-4967, Vol. 30, no 2, 216-236 p.Article in journal (Refereed)
    Abstract [en]

    An increasing number of robots for outdoor applications rely on complex three-dimensional (3D) environmental models. In many cases, 3D maps are used for vital tasks, such as path planning and collision detection in challenging semistructured environments. Thus, acquiring accurate three-dimensional maps is an important research topic of high priority for autonomously navigating robots. This article proposes an evaluation method that is designed to compare the consistency with which different representations model the environment. In particular, the article examines several popular (probabilistic) spatial representations that are capable of predicting the occupancy of any point in space, given prior 3D range measurements. This work proposes to reformulate the obtained environmental models as probabilistic binary classifiers, thus allowing for the use of standard evaluation and comparison procedures. To avoid introducing localization errors, this article concentrates on evaluating models constructed from measurements acquired at fixed sensor poses. Using a cross-validation approach, the consistency of different representations, i.e., the likelihood of correctly predicting unseen measurements in the sensor field of view, can be evaluated. Simulated and real-world data sets are used to benchmark the precision of four spatial models—occupancy grid, triangle mesh, and two variations of the three-dimensional normal distributions transform (3D-NDT)—over various environments and sensor noise levels. Overall, the consistency of representation of the 3D-NDT is found to be the highest among the tested models, with a similar performance over varying input data.

  • 39.
    Stoyanov, Todor
    et al.
    Örebro University, School of Science and Technology.
    Magnusson, Martin
    Örebro University, School of Science and Technology.
    Lilienthal, Achim J.
    Örebro University, School of Science and Technology.
    Point Set Registration through Minimization of the L-2 Distance between 3D-NDT Models2012In: 2012 IEEE International Conference on Robotics and Automation (ICRA), IEEE conference proceedings, 2012, 5196-5201 p.Conference paper (Refereed)
    Abstract [en]

    Point set registration — the task of finding the best fitting alignment between two sets of point samples, is an important problem in mobile robotics. This article proposes a novel registration algorithm, based on the distance between Three- Dimensional Normal Distributions Transforms. 3D-NDT models — a sub-class of Gaussian Mixture Models with uniformly weighted, largely disjoint components, can be quickly computed from range point data. The proposed algorithm constructs 3DNDT representations of the input point sets and then formulates an objective function based on the L2 distance between the considered models. Analytic first and second order derivatives of the objective function are computed and used in a standard Newton method optimization scheme, to obtain the best-fitting transformation. The proposed algorithm is evaluated and shown to be more accurate and faster, compared to a state of the art implementation of the Iterative Closest Point and 3D-NDT Point-to-Distribution algorithms.

  • 40.
    Stoyanov, Todor
    et al.
    Örebro University, School of Science and Technology.
    Magnusson, Martin
    Örebro University, School of Science and Technology.
    Lilienthal, Achim J.
    Örebro University, School of Science and Technology.
    Andreasson, Henrik
    Örebro University, School of Science and Technology.
    Fast and accurate scan registration through minimization of the distance between compact 3D NDT Representations2012In: The international journal of robotics research, ISSN 0278-3649, E-ISSN 1741-3176, Vol. 31, no 12, 1377-1393 p.Article in journal (Refereed)
    Abstract [en]

    Registration of range sensor measurements is an important task in mobile robotics and has received a lot of attention. Several iterative optimization schemes have been proposed in order to align three-dimensional (3D) point scans. With the more widespread use of high-frame-rate 3D sensors and increasingly more challenging application scenarios for mobile robots, there is a need for fast and accurate registration methods that current state-of-the-art algorithms cannot always meet. This work proposes a novel algorithm that achieves accurate point cloud registration an order of a magnitude faster than the current state of the art. The speedup is achieved through the use of a compact spatial representation: the Three-Dimensional Normal Distributions Transform (3D-NDT). In addition, a fast, global-descriptor based on the 3D-NDT is defined and used to achieve reliable initial poses for the iterative algorithm. Finally, a closed-form expression for the covariance of the proposed method is also derived. The proposed algorithms are evaluated on two standard point cloud data sets, resulting in stable performance on a par with or better than the state of the art. The implementation is available as an open-source package for the Robot Operating system (ROS).

  • 41.
    Stoyanov, Todor
    et al.
    Örebro University, School of Science and Technology.
    Mojtahedzadeh, Rasoul
    Örebro University, School of Science and Technology.
    Andreasson, Henrik
    Örebro University, School of Science and Technology.
    Lilienthal, Achim J.
    Örebro University, School of Science and Technology.
    Comparative evaluation of range sensor accuracy for indoor mobile robotics and automated logistics applications2013In: Robotics and Autonomous Systems, ISSN 0921-8890, E-ISSN 1872-793X, Vol. 61, no 10, 1094-1105 p.Article in journal (Refereed)
    Abstract [en]

    3D range sensing is an important topic in robotics, as it is a component in vital autonomous subsystems such as for collision avoidance, mapping and perception. The development of affordable, high frame rate and precise 3D range sensors is thus of considerable interest. Recent advances in sensing technology have produced several novel sensors that attempt to meet these requirements. This work is concerned with the development of a holistic method for accuracy evaluation of the measurements produced by such devices. A method for comparison of range sensor output to a set of reference distance measurements, without using a precise ground truth environment model, is proposed. This article presents an extensive evaluation of three novel depth sensors — the Swiss Ranger SR-4000, Fotonic B70 and Microsoft Kinect. Tests are concentrated on the automated logistics scenario of container unloading. Six different setups of box-, cylinder-, and sack-shaped goods inside a mock-up container are used to collect range measurements. Comparisons are performed against hand-crafted ground truth data, as well as against a reference actuated Laser Range Finder (aLRF) system. Additional test cases in an uncontrolled indoor environment are performed in order to evaluate the sensors’ performance in a challenging, realistic application scenario.

  • 42.
    Stoyanov, Todor
    et al.
    Örebro University, School of Science and Technology.
    Saarinen, Jari
    Örebro University, School of Science and Technology.
    Andreasson, Henrik
    Örebro University, School of Science and Technology.
    Lilienthal, Achim J.
    Örebro University, School of Science and Technology.
    Normal distributions transform occupancy map fusion: simultaneous mapping and tracking in large scale dynamic environments2013In: Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), IEEE, 2013, 4702-4708 p.Conference paper (Refereed)
  • 43.
    Stoyanov, Todor
    et al.
    Örebro University, School of Science and Technology.
    Vaskevicius, Narunas
    Jacobs University Bremen, Bremen, Germany.
    Mueller, Christian Atanas
    Jacobs University Bremen, Bremen, Germany.
    Fromm, Tobias
    Jacobs University Bremen, Bremen, Germany.
    Krug, Robert
    Örebro University, School of Science and Technology.
    Tincani, Vinicio
    University of Pisa, Pisa, Italy.
    Mojtahedzadeh, Rasoul
    Örebro University, School of Science and Technology.
    Kunaschk, Stefan
    Bremer Institut für Produktion und Logistik (BIBA), Bremen, Germany.
    Ernits, R. Mortensen
    Bremer Institut für Produktion und Logistik (BIBA), Bremen, Germany.
    Canelhas, Daniel R.
    Örebro University, School of Science and Technology.
    Bonilla, Manuell
    University of Pisa, Pisa, Italy.
    Schwertfeger, Soeren
    ShanghaiTech University, Shanghai, China.
    Bonini, Marco
    Reutlingen University, Reutlingen, Germany.
    Halfar, Harry
    Reutlingen University, Reutlingen, Germany.
    Pathak, Kaustubh
    Jacobs University Bremen, Bremen, Germany.
    Rohde, Moritz
    Bremer Institut für Produktion und Logistik (BIBA), Bremen, Germany.
    Fantoni, Gualtiero
    University of Pisa, Pisa, Italy.
    Bicchi, Antonio
    Università di Pisa & Istituto Italiano di Tecnologia, Genova, Italy.
    Birk, Andreas
    Jacobs University, Bremen, Germany.
    Lilienthal, Achim J.
    Örebro University, School of Science and Technology.
    Echelmeyer, Wolfgang
    Reutlingen University, Reutlingen, Germany.
    No More Heavy Lifting: Robotic Solutions to the Container-Unloading Problem2016In: IEEE robotics & automation magazine, ISSN 1070-9932, E-ISSN 1558-223X, Vol. 23, no 4, 94-106 p.Article in journal (Refereed)
  • 44.
    Tincani, Vinicio
    et al.
    University of Pisa, Pisa, Italy.
    Catalano, Manuel
    University of Pisa, Pisa, Italy.
    Grioli, Giorgio
    University of Pisa, Pisa, Italy.
    Stoyanov, Todor
    Örebro University, School of Science and Technology.
    Krug, Robert
    Örebro University, School of Science and Technology.
    Lilienthal, Achim J.
    Örebro University, School of Science and Technology.
    Fantoni, Gualtiero
    University of Pisa, Pisa, Italy.
    Bicchi, Antonio
    University of Pisa, Pisa, Italy; Department of Advanced Robotics, Istituto Italiano di Tecnologia, Genova, Italy.
    Sensitive Active Surfaces on the Velvet II Dexterous Gripper2015Conference paper (Refereed)
  • 45.
    Tincani, Vinicio
    et al.
    University of Pisa, Pisa, Italy.
    Stoyanov, Todor
    Örebro University, School of Science and Technology.
    Krug, Robert
    Örebro University, School of Science and Technology.
    Catalano, Manuel
    University of Pisa, Pisa, Italy.
    Grioli, Giorgio
    University of Pisa, Pisa, Italy.
    Lilienthal, Achim J.
    Örebro University, School of Science and Technology.
    Fantoni, Gualtiero
    University of Pisa, Pisa, Italy.
    Bicchi, Antonio
    Istituto Italiano di Tecnologia, Genoa, Italy.
    The Grasp Acquisition Strategy of the Velvet II2015Conference paper (Refereed)
  • 46.
    Vaskevicius, N.
    et al.
    Jacobs University, Bremen, Germany.
    Mueller, C. A.
    Jacobs University, Bremen, Germany.
    Bonilla, M.
    University of Pisa, Italy.
    Tincani, V.
    University of Pisa, Italy.
    Stoyanov, Todor
    Örebro University, School of Science and Technology.
    Fantoni, G.
    University of Pisa, Italy.
    Pathak, K.
    Jacobs University, Bremen, Germany.
    Lilienthal, Achim J.
    Örebro University, School of Science and Technology.
    Bicchi, A.
    University of Pisa, Italy.
    Birk, A.
    Jacobs University, Bremen, Germany.
    Object recognition and localization for robust grasping with a dexterous gripper in the context of container unloading2014Conference paper (Refereed)
    Abstract [en]

    The work presented here is embedded in research on an industrial application scenario, namely autonomous shipping-container unloading, which has several challenging constraints: the scene is very cluttered, objects can be much larger than in common table-top scenarios; the perception must be highly robust, while being as fast as possible. These contradicting goals force a compromise between speed and accuracy. In this work, we investigate a state of the art perception system integrated with a dexterous gripper. In particular, we are interested in pose estimation errors from the recognition module and whether these errors can be handled by the abilities of the gripper.

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