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  • 1.
    Abdul Khaliq, Ali
    et al.
    Örebro University, School of Science and Technology.
    Pecora, Federico
    Örebro University, School of Science and Technology.
    Saffiotti, Alessandro
    Örebro University, School of Science and Technology.
    Point-to-point safe navigation of a mobile robot using stigmergy and RFID technology2016In: 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Institute of Electrical and Electronics Engineers (IEEE), 2016, p. 1497-1504, article id 7759243Conference paper (Refereed)
    Abstract [en]

    Reliable autonomous navigation is still a challenging problem for robots with simple and inexpensive hardware. A key difficulty is the need to maintain an internal map of the environment and an accurate estimate of the robot’s position in this map. Recently, a stigmergic approach has been proposed in which a navigation map is stored into the environment, on a grid of RFID tags, and robots use it to optimally reach predefined goal points without the need for internal maps. While effective,this approach is limited to a predefined set of goal points. In this paper, we extend this approach to enable robots to travel to any point on the RFID floor, even if it was not previously identified as a goal location, as well as to keep a safe distance from any given critical location. Our approach produces safe, repeatable and quasi-optimal trajectories without the use of internal maps, self localization, or path planning. We report experiments run in a real apartment equipped with an RFID floor, in which a service robot either reaches or avoids a user who wears slippers equipped with an RFID tag reader.

  • 2.
    Abdullah, Muhammad
    Örebro University, School of Science and Technology.
    Mobile Robot Navigation using potential fields andmarket based optimization2013Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    A team of mobile robots moving in a shared area raises the problem of safe and autonomous navigation. While avoiding static and dynamic obstacles, mobile robots in a team can lead to complicated and irregular movements. Local reactive approaches are used to deal with situations where robots are moving in dynamic environment; these approaches help in safe navigation of robots but do not give optimal solution. In this work a 2-D navigation strategy is implemented, where a potential field method is used for obstacle avoidance. This potential field method is improved using fuzzy rules, traffic rules and market based optimization (MBO). Fuzzy rules are used to deform repulsive potential fields in the vicinity of obstacles. Traffic rules are used to deal situations where two robots are crossing each other. Market based optimization (MBO) is used to strengthen or weaken repulsive potential fields generated by other robots based on their importance. For the verification of this strategy on more realistic vehicles this navigation strategy is implemented and tested in simulation. Issues while implementing this method and limitations of this navigation strategy are also discussed. Extensive experiments are performed to examine the validity of MBO navigation strategy over traditional potential field (PF) method.

  • 3.
    Amato, Giuseppe
    et al.
    ISTI-CNR, Pisa, Italy.
    Broxvall, Mathias
    Örebro University, School of Science and Technology.
    Chessa, Stefano
    Università di Pisa, Pisa, Italy.
    Dragone, Mauro
    University College Dublin, Dublin, Ireland.
    Gennaro, Caludio
    ISTI-CNR, Pisa, Italy.
    Lopez, Rafa
    Robotnik Automation, Valencia, Spain.
    Maguire, Liam
    University of Ulster, Coleraine, Ireland.
    McGinnity, Martin T.
    University of Ulster, Coleraine, Ireland.
    Micheli, Alessio
    Università di Pisa, Pisa, Italy.
    Renteria, Arantxa
    Tecnalia, Derio, Spain.
    O’Hare, Gregory M. P.
    University College Dublin, Dublin, Ireland.
    Pecora, Federico
    Örebro University, School of Science and Technology.
    Robotic UBIquitous COgnitive Network2012In: Ambient Intelligence: Software and Applications / [ed] Paulo Novais, Kasper Hallenborg, Dante I. Tapia, Juan M. Corchado Rodríguez, Springer-Verlag New York, 2012, p. 191-195Conference paper (Refereed)
    Abstract [en]

    Robotic ecologies are networks of heterogeneous robotic devices pervasively embedded in everyday environments, where they cooperate to perform complex tasks. While their potential makes them increasingly popular, one fundamental problem is how to make them self-adaptive, so as to reduce the amount of preparation, pre-programming and human supervision that they require in real world applications. The EU FP7 project RUBICON develops self-sustaining learning solutions yielding cheaper, adaptive and efficient coordination of robotic ecologies. The approach we pursue builds upon a unique combination of methods from cognitive robotics, agent control systems, wireless sensor networks and machine learning. This paper briefly illustrates how these techniques are being extended, integrated, and applied to AAL applications.

  • 4.
    Andreasson, Henrik
    et al.
    Örebro University, School of Science and Technology.
    Adolfsson, Daniel
    Örebro University, School of Science and Technology.
    Stoyanov, Todor
    Örebro University, School of Science and Technology.
    Magnusson, Martin
    Örebro University, School of Science and Technology.
    Lilienthal, Achim
    Örebro University, School of Science and Technology.
    Incorporating Ego-motion Uncertainty Estimates in Range Data Registration2017In: 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Institute of Electrical and Electronics Engineers (IEEE), 2017, p. 1389-1395Conference paper (Refereed)
    Abstract [en]

    Local scan registration approaches commonlyonly utilize ego-motion estimates (e.g. odometry) as aninitial pose guess in an iterative alignment procedure. Thispaper describes a new method to incorporate ego-motionestimates, including uncertainty, into the objective function of aregistration algorithm. The proposed approach is particularlysuited for feature-poor and self-similar environments,which typically present challenges to current state of theart registration algorithms. Experimental evaluation showssignificant improvements in accuracy when using data acquiredby Automatic Guided Vehicles (AGVs) in industrial productionand warehouse environments.

  • 5.
    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
    nria Grenoble Rhône-Alpes, Meylan-Montbonnot, 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, Espo, 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, E-ISSN 1558-223X, Vol. 22, no 1, p. 64-75Article 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.

  • 6.
    Arain, Muhammad Asif
    Mehran University of Engineering & Technology, Pakistan.
    Navobot formula 2: a navigation and handling implementation2006Conference paper (Refereed)
  • 7.
    Arain, Muhammad Asif
    et al.
    Mehran University of Engineering & Technology, Pakistan.
    Ansari, Muhammad Adil
    Khatri, Chandan Kumar
    Maheshwari, Bheesham Kumar
    Kazi, Sheryar Anwer
    Design, Mathematical Modeling & Simulation of a Robot System with 3-DOF2005Conference paper (Refereed)
  • 8.
    Arain, Muhammad Asif
    et al.
    Örebro University, School of Science and Technology.
    Fan, Han
    Örebro University, School of Science and Technology.
    Hernandez Bennetts, Victor
    Örebro University, School of Science and Technology.
    Schaffernicht, Erik
    Örebro University, School of Science and Technology.
    Lilienthal, Achim J.
    Örebro University, School of Science and Technology.
    Improving Gas Tomography With Mobile Robots: An Evaluation of Sensing Geometries in Complex Environments2017In: 2017 ISOCS/IEEE International Symposium on Olfaction andElectronic Nose (ISOEN 2017) Proceedings, 2017, article id 7968895Conference paper (Refereed)
    Abstract [en]

    An accurate model of gas emissions is of high importance in several real-world applications related to monitoring and surveillance. Gas tomography is a non-intrusive optical method to estimate the spatial distribution of gas concentrations using remote sensors. The choice of sensing geometry, which is the arrangement of sensing positions to perform gas tomography, directly affects the reconstruction quality of the obtained gas distribution maps. In this paper, we present an investigation of criteria that allow to determine suitable sensing geometries for gas tomography. We consider an actuated remote gas sensor installed on a mobile robot, and evaluated a large number of sensing configurations. Experiments in complex settings were conducted using a state-of-the-art CFD-based filament gas dispersal simulator. Our quantitative comparison yields preferred sensing geometries for sensor planning, which allows to better reconstruct gas distributions.

  • 9.
    Arain, Muhammad Asif
    et al.
    Örebro University, School of Science and Technology.
    Schaffernicht, Erik
    Örebro University, School of Science and Technology.
    Hernandez Bennetts, Victor
    Örebro University, School of Science and Technology.
    Lilienthal, Achim J.
    Örebro University, School of Science and Technology.
    The Right Direction to Smell: Efficient Sensor Planning Strategies for Robot Assisted Gas Tomography2016In: 2016 IEEE International Conference on Robotics and Automation (ICRA), New York, USA: IEEE Robotics and Automation Society, 2016, p. 4275-4281Conference paper (Refereed)
    Abstract [en]

    Creating an accurate model of gas emissions is an important task in monitoring and surveillance applications. A promising solution for a range of real-world applications are gas-sensitive mobile robots with spectroscopy-based remote sensors that are used to create a tomographic reconstruction of the gas distribution. The quality of these reconstructions depends crucially on the chosen sensing geometry. In this paper we address the problem of sensor planning by investigating sensing geometries that minimize reconstruction errors, and then formulate an optimization algorithm that chooses sensing configurations accordingly. The algorithm decouples sensor planning for single high concentration regions (hotspots) and subsequently fuses the individual solutions to a global solution consisting of sensing poses and the shortest path between them. The proposed algorithm compares favorably to a template matching technique in a simple simulation and in a real-world experiment. In the latter, we also compare the proposed sensor planning strategy to the sensing strategy of a human expert and find indications that the quality of the reconstructed map is higher with the proposed algorithm.

  • 10.
    Asadi, Sahar
    et al.
    Örebro University, School of Science and Technology.
    Pashami, Sepideh
    Örebro University, School of Science and Technology.
    Loutfi, Amy
    Örebro University, School of Science and Technology.
    Lilienthal, Achim J.
    Örebro University, School of Science and Technology.
    TD Kernel DM+V: time-dependent statistical gas distribution modelling on simulated measurements2011In: Olfaction and Electronic Nose: proceedings of the 14th International Symposium on Olfaction and Electronic Nose (ISOEN) / [ed] Perena Gouma, Springer Science+Business Media B.V., 2011, p. 281-282Conference paper (Refereed)
    Abstract [en]

    To study gas dispersion, several statistical gas distribution modelling approaches have been proposed recently. A crucial assumption in these approaches is that gas distribution models are learned from measurements that are generated by a time-invariant random process. While a time-independent random process can capture certain fluctuations in the gas distribution, more accurate models can be obtained by modelling changes in the random process over time. In this work we propose a time-scale parameter that relates the age of measurements to their validity for building the gas distribution model in a recency function. The parameters of the recency function define a time-scale and can be learned. The time-scale represents a compromise between two conflicting requirements for obtaining accurate gas distribution models: using as many measurements as possible and using only very recent measurements. We have studied several recency functions in a time-dependent extension of the Kernel DM+V algorithm (TD Kernel DM+V). Based on real-world experiments and simulations of gas dispersal (presented in this paper) we demonstrate that TD Kernel DM+V improves the obtained gas distribution models in dynamic situations. This represents an important step towards statistical modelling of evolving gas distributions.

  • 11. Bacciu, D.
    et al.
    Broxvall, Mathias
    Örebro University, School of Science and Technology.
    Coleman, S.
    Dragone, M.
    Gallicchio, C.
    Gennaro, C.
    Guzmán, R.
    Lopez, R.
    Lozano-Peiteado, H.
    Ray, A.
    Renteria, A.
    Saffiotti, Alessandro
    Örebro University, School of Science and Technology.
    Vairo, C.
    Self-sustaining learning for robotic ecologies2012Conference paper (Refereed)
    Abstract [en]

    The most common use of wireless sensor networks (WSNs) is to collect environmental data from a specificarea, and to channel it to a central processing node for on-line or off-line analysis. The WSN technology,however, can be used for much more ambitious goals. We claim that merging the concepts and technology ofWSN with the concepts and technology of distributed robotics and multi-agent systems can open new waysto design systems able to provide intelligent services in our homes and working places. We also claim thatendowing these systems with learning capabilities can greatly increase their viability and acceptability, bysimplifying design, customization and adaptation to changing user needs. To support these claims, we illus-trate our architecture for an adaptive robotic ecology, named RUBICON, consisting of a network of sensors,effectors and mobile robots.

  • 12.
    Bacciu, Davide
    et al.
    Dipartimento di Informatica, Università di Pisa, Pisa, Italy.
    Gallicchio, Claudio
    Dipartimento di Informatica, Università di Pisa, Pisa, Italy.
    Micheli, Alessio
    Dipartimento di Informatica, Università di Pisa, Pisa, Italy.
    Di Rocco, Maurizio
    Örebro University, School of Science and Technology.
    Saffiotti, Alessandro
    Örebro University, School of Science and Technology.
    Learning context-aware mobile robot navigation in home environments2014In: IISA 2014: The 5th International Conference on Information, Intelligence, Systems and Applications, New York: Institute of Electrical and Electronics Engineers (IEEE), 2014, p. 57-62, article id 6878733Conference paper (Refereed)
    Abstract [en]

    We present an approach to make planning adaptive in order to enable context-aware mobile robot navigation. We integrate a model-based planner with a distributed learning system based on reservoir computing, to yield personalized planning and resource allocations that account for user preferences and environmental changes. We demonstrate our approach in a real robot ecology, and show that the learning system can effectively exploit historical data about navigation performance to modify the models in the planner, without any prior information oncerning the phenomenon being modeled. The plans produced by the adapted CL fail more rarely than the ones generated by a non-adaptive planner. The distributed learning system handles the new learning task autonomously, and is able to automatically identify the sensorial information most relevant for the task, thus reducing the communication and computational overhead of the predictive task.

  • 13.
    Beeson, Patrick
    et al.
    TRACLabs Inc., Webster TX, USA.
    Kortenkamp, David
    TRACLabs Inc., Webster TX, USA.
    Bonasso, R. Peter
    TRACLabs Inc., Webster TX, USA.
    Persson, Andreas
    Örebro University, School of Science and Technology.
    Loutfi, Amy
    Örebro University, School of Science and Technology.
    Bona, Jonathan P
    State University of New York, Buffalo, USA.
    An Ontology-Based Symbol Grounding System for Human-Robot Interaction2014In: Artificial Intelligence for Human-Robot Interaction: 2014 AAAI Fall Symposium, AAAI Press, 2014Conference paper (Refereed)
    Abstract [en]

    This paper presents an ongoing collaboration to develop a perceptual anchoring framework which creates and maintains the symbol-percept links concerning household objects. The paper presents an approach to non-trivialize the symbol system using ontologies and allow for HRI via enabling queries about objects properties, their affordances, and their perceptual characteristics as viewed from the robot (e.g. last seen). This position paper describes in brief the objective of creating a long term perceptual anchoring framework for HRI and outlines the preliminary work done this far.

  • 14.
    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, p. 6362-6367Conference 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.

  • 15.
    Bennewitz, Maren
    et al.
    University of Freiburg.
    Burgard, Wolfram
    University of Freiburg.
    Cielniak, Grzegorz
    Örebro University, Department of Technology.
    Thrun, Sebastian
    Carnegie Mellon University.
    Learning motion patterns of people for compliant robot motion2005In: The international journal of robotics research, ISSN 0278-3649, E-ISSN 1741-3176, Vol. 24, no 1, p. 31-48Article in journal (Refereed)
    Abstract [en]

    Whenever people move through their environments they do not move randomly. Instead, they usually follow specific trajectories or motion patterns corresponding to their intentions. Knowledge about such patterns enables a mobile robot to robustly keep track of persons in its environment and to improve its behavior. This paper proposes a technique for learning collections of trajectories that characterize typical motion patterns of persons. Data recorded with laser-range finders is clustered using the expectation maximization algorithm. Based on the result of the clustering process we derive a Hidden Markov Model (HMM) that is applied to estimate the current and future positions of persons based on sensory input. We also describe how to incorporate the probabilistic belief about the potential trajectories of persons into the path planning process. We present several experiments carried out in different environments with a mobile robot equipped with a laser range scanner and a camera system. The results demonstrate that our approach can reliably learn motion patterns of persons, can robustly estimate and predict positions of persons, and can be used to improve the navigation behavior of a mobile robot.

  • 16.
    Berna, Amalia
    et al.
    CSIRO Ecosystem Sciences and CSIRO Food Futures Flagship, Canberra, Australian Capital Territory (ACT), Australia.
    Vergara, Alexander
    University of California, San Diego, USA.
    Trincavelli, Marco
    Örebro University, School of Science and Technology.
    Huerta, Ramon
    University of California, San Diego, USA.
    Afonja, Ayo
    Department of Chemistry, University College London, London, UK.
    Parkin, Ivan
    Binions, Russell
    Trowell, Stephen
    Evaluating zeolite-modified sensors: towards a faster set of chemical sensors2011In: Olfaction and electronic nose: proceedings of the 14th International Symposium on Olfaction and Electronic Nose (ISOEN 2011), May 2-5, 2011, New York City, USA, American Institute of Physics (AIP), 2011, p. 50-52Conference paper (Refereed)
    Abstract [en]

    The response of zeolite-modified sensors, prepared by screen printing layers of chromium titanium oxide (CTO), were compared to unmodified tin oxide sensors using amplitude and transient responses. For transient responses we used a family of features, derived from the exponential moving average (EMA), to characterize chemo-resistive responses. All sensors were tested simultaneously against 20 individual volatile compounds from four chemical groups. The responses of the two types of sensors showed some independence. The zeolite modified CTO sensors discriminated compounds better using either amplitude response or EMA features and CTO-modified sensors also responded three times faster.

  • 17. 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, p. 463-472Conference 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.

  • 18. 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)
  • 19.
    Bonaccorsi, Manuele
    et al.
    The BioRobotics Institute, Scuola Superiore Sant’Anna, Pisa, Italy.
    Fiorini, Laura
    The BioRobotics Institute, Scuola Superiore Sant’Anna, Pisa, Italy.
    Cavallo, Filippo
    The BioRobotics Institute, Scuola Superiore Sant’Anna, Pisa, Italy.
    Saffiotti, Alessandro
    Örebro University, School of Science and Technology.
    Dario, Paolo
    The BioRobotics Institute, Scuola Superiore Sant’Anna, Pisa, Italy.
    A cloud robotics solution to improve social assistive robots for active and healthy aging2016In: International Journal of Social Robotics, ISSN 1875-4791, E-ISSN 1875-4805, Vol. 8, no 3, p. 393-408Article in journal (Refereed)
    Abstract [en]

    Technological innovation in robotics and ICT represents an effective solution to tackle the challenge of providing social sustainable care services for the ageing population. The recent introduction of cloud technologies is opening new opportunities for the provisioning of advanced robotic services based on the cooperation of a number of connected robots, smart environments and devices improved by the huge cloud computational and storage capability. In this context, this paper aims to investigate and assess the potentialities of a cloud robotic system for the provisioning of assistive services for the promotion of active and healthy ageing. The system comprised two different smart environments, located in Italy and Sweden, where a service robot is connected to a cloud platform for the provisioning of localization based services to the users. The cloud robotic services were tested in the two realistic environments to assess the general feasibility of the solution and demonstrate the ability to provide assistive location based services in a multiple environment framework. The results confirmed the validity of the solution but also suggested a deeper investigation on the dependability of the communication technologies adopted in such kind of systems.

  • 20. Canelhas, Daniel Ricão
    et al.
    Stoyanov, Todor
    Örebro University, School of Science and Technology.
    Lilienthal, Achim J.
    Örebro University, School of Science and Technology.
    A Survey of Voxel Interpolation Methods and an Evaluation of Their Impact on Volumetric Map-Based Visual Odometry2018In: Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Brisbane, May 21 - 25, 2018, 2018Conference paper (Refereed)
    Abstract [en]

    Voxel volumes are simple to implement and lend themselves to many of the tools and algorithms available for 2D images. However, the additional dimension of voxels may be costly to manage in memory when mapping large spaces at high resolutions. While lowering the resolution and using interpolation is common work-around, in the literature we often find that authors either use trilinear interpolation or nearest neighbors and rarely any of the intermediate options. This paper presents a survey of geometric interpolation methods for voxel-based map representations. In particular we study the truncated signed distance field (TSDF) and the impact of using fewer than 8 samples to perform interpolation within a depth-camera pose tracking and mapping scenario. We find that lowering the number of samples fetched to perform the interpolation results in performance similar to the commonly used trilinear interpolation method, but leads to higher framerates. We also report that lower bit-depth generally leads to performance degradation, though not as much as may be expected, with voxels containing as few as 3 bits sometimes resulting in adequate estimation of camera trajectories.

  • 21.
    Carletti, Cristina
    et al.
    Marche Polytechnic University Ancona, Ancona, Italy.
    Di Rocco, Maurizio
    Roma Tre University, Rome, Italy.
    Gasparri, Andrea
    Roma Tre University, Rome, Italy.
    Ulivi, Giovanni
    Roma Tre University, Rome, Italy.
    A distributed transferable belief model for collaborative topological map-building in multi-robot systems2010In: 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), IEEE, 2010, p. 554-560Conference paper (Refereed)
    Abstract [en]

    In this paper the problem of multi-robot collaborative topological map-building is addressed. In this framework, a team of robots is supposed to move in an indoor office-like environment. Each robot, after building a local map by using infrared range-finders, achieves a topological representation of the environment by extracting the most significant features via the Hough transform and comparing them with a set of predefined environmental patterns. The local view of each robot which is significantly constrained by its limited sensing capabilities is then strengthened by a collaborative aggregation schema based on the Transferable Belief Model (TBM). In this way, a better representation of the environment is achieved by each robot with a minimal exchange of information. A preliminary experimental validation carried out by exploiting data collected from a self-made team of robots is proposed.

  • 22. 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)
  • 23.
    Charusta, Krzysztof
    et al.
    Örebro University, School of Science and Technology.
    Krug, Robert
    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.
    Independent contact regions based on a patch contact model2012In: 2012 IEEE International Conference on Robotics and Automation (ICRA), IEEE conference proceedings, 2012, p. 4162-4169Conference paper (Refereed)
    Abstract [en]

    The synthesis of multi-fingered grasps on nontrivial objects requires a realistic representation of the contact between the fingers of a robotic hand and an object. In this work, we use a patch contact model to approximate the contact between a rigid object and a deformable anthropomorphic finger. This contact model is utilized in the computation of Independent Contact Regions (ICRs) that have been proposed as a way to compensate for shortcomings in the finger positioning accuracy of robotic grasping devices. We extend the ICR algorithm to account for the patch contact model and show the benefits of this solution.

  • 24.
    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, p. 1338-1344Conference 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.

  • 25.
    Cirillo, Marcello
    et al.
    Örebro University, School of Science and Technology.
    Pecora, Federico
    Örebro University, School of Science and Technology.
    Andreasson, Henrik
    Örebro University, School of Science and Technology.
    Uras, Tansel
    Department of Computer Science, University of Southern California, USA.
    Koenig, Sven
    Department of Computer Science, University of Southern California, USA.
    Integrated Motion Planning and Coordination for Industrial Vehicles2014In: Proceedings of the 24th International Conference on Automated Planning and Scheduling, 2014Conference paper (Refereed)
    Abstract [en]

    A growing interest in the industrial sector for autonomous ground vehicles has prompted significant investment in fleet management systems. Such systems need to accommodate on-line externally imposed temporal and spatial requirements, and to adhere to them even in the presence of contingencies. Moreover, a fleet management system should ensure correctness, i.e., refuse to commit to requirements that cannot be satisfied. We present an approach to obtain sets of alternative execution patterns (called trajectory envelopes) which provide these guarantees. The approach relies on a constraint-based representation shared among multiple solvers, each of which progressively refines trajectory envelopes following a least commitment principle.

  • 26.
    Cirillo, Marcello
    et al.
    Örebro University, School of Science and Technology.
    Uras, Tansel
    Department of Computer Science, University of Southern California, USA.
    Koenig, Sven
    Department of Computer Science, University of Southern California, USA.
    A lattice-based approach to multi-robot motion planning for non-holonomic vehicles2014In: Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2014, p. 232-239Conference paper (Refereed)
    Abstract [en]

    Coordinating fleets of autonomous, non-holonomic vehicles is paramount to many industrial applications. While there exists solutions to efficiently calculate trajectories for individual vehicles, an effective methodology to coordinate their motions and to avoid deadlocks is still missing. Decoupled approaches, where motions are calculated independently for each vehicle and then centrally coordinated for execution, have the means to identify deadlocks, but not to solve all of them. We present a novel approach that overcomes this limitation and that can be used to complement the deficiencies of decoupled solutions with centralized coordination. Here, we formally define an extension of the framework of lattice-based motion planning to multi-robot systems and we validate it experimentally. Our approach can jointly plan for multiple vehicles and it generates kinematically feasible and deadlock-free motions.

  • 27.
    Coradeschi, Silvia
    et al.
    Örebro University, School of Science and Technology.
    Loutfi, Amy
    Örebro University, School of Science and Technology.
    Kristoffersson, Annica
    Örebro University, School of Science and Technology.
    Cortellessa, Gabriella
    Consiglio Nazionale delle Ricerche (CNR), Rome, Italy; Istituto di Scienze e Tecnologie della Cognizione (ISTC-CNR), Rome, Italy.
    Severinson Eklundh, Kerstin
    KTH, Royal Institute of Technology, Stockholm, Sweden.
    Social robotic telepresence2011In: the 6th ACM/IEEE International Conference on Human-Robot Interaction (HRI 2011).HRI, ACM Digital Library , 2011, p. 5-6Conference paper (Refereed)
  • 28.
    Dandan, Kinan
    et al.
    Örebro University, School of Science and Technology.
    Ananiev, Anani
    Örebro University, School of Science and Technology.
    Ivan, Kalaykov
    Örebro University, School of Science and Technology.
    SIRO: the silos surface cleaning robot concept2013Conference paper (Refereed)
    Abstract [en]

    A concept of a suspended robot for surface cleaning in silos is presented in this paper. The main requirements and limitations resulting from the specific operational conditions are discussed. Due to the large dimension of the silo as a confined space, specific kinematics of the robot manipulator is proposed. The major problems in its design are highlighted and an approach to resolve them is proposed. The suggested concept is a reasonable compromise between the basic contradicting factors in the design: small entrance and large surface of the confined space, suspension and stabilization of the robot

  • 29.
    Daoutis, Marios
    et al.
    Örebro University, School of Science and Technology.
    Coradeschi, Silvia
    Örebro University, School of Science and Technology.
    Loutfi, Amy
    Örebro University, School of Science and Technology.
    Towards concept anchoring for cognitive robots2012In: Intelligent Service Robotics, ISSN 1861-2784, Vol. 5, no 4, p. 213-228Article in journal (Refereed)
    Abstract [en]

    We present a model for anchoring categorical conceptual information which originates from physical perception and the web. The model is an extension of the anchoring framework which is used to create and maintain over time semantically grounded sensor information. Using the augmented anchoring framework that employs complex symbolic knowledge from a commonsense knowledge base, we attempt to ground and integrate symbolic and perceptual data that are available on the web. We introduce conceptual anchors which are representations of general, concrete conceptual terms. We show in an example scenario how conceptual anchors can be coherently integrated with perceptual anchors and commonsense information for the acquisition of novel concepts.

  • 30.
    Daoutis, Marios
    et al.
    Örebro University, School of Science and Technology.
    Mavridis, Nikolaos
    Towards a Model for Grounding Semantic Composition2014Conference paper (Refereed)
  • 31.
    Di Rocco, Maurizio
    Roma Tre University.
    Formation control through environment pattern recognition for a multi-robotarchitecture2009Conference paper (Refereed)
  • 32.
    Di Rocco, Maurizio
    et al.
    Örebro University, School of Science and Technology. Roma Tre University, Rome, Italy.
    La Gala, Francesco
    Marine Technology Research Institute (INSEAN), Rome, Italy.
    Ulivi, Giovanni
    Roma Tre University, Rome, Italy.
    Testing Multirobot Algorithms SAETTA: A Small and Cheap Mobile Unit2013In: IEEE robotics & automation magazine, ISSN 1070-9932, E-ISSN 1558-223X, Vol. 20, no 2, p. 52-62Article in journal (Other academic)
  • 33.
    Di Rocco, Maurizio
    et al.
    Roma Tre University, Rome, Italy.
    Pascucci, Federica
    Probabilistic localization in sensor networks using distributed Kalman filter2010In: 7th IFAC Symposium on Intelligent Autonomous Vehicles 2010, Lecce, Italy / [ed] Giovanni Indiveri, Antonio M. Pascoal, 2010Conference paper (Refereed)
    Abstract [en]

    In recent years sensor networks have interested fields such as environment monitoring, surveillance and other distributed applications for data elaboration. This interest has been based on the decentralized approach in treating the information. However it is still a challenge to manipulate such streams of data when the dimension of the net becomes large despite computational capabilities and consumption constraints. In most of applications, location awareness is fundamental to accomplish common tasks. In this paper a probabilistic approach to solve localization problem in wireless sensor networks is presented. The algorithm, based on the Kalman Filter, estimates the sensors' location by an adaptive behavior. The technique proposed allows a reduction of the computation burden respect to the traditional Kalman Filter showing, as explained in simulations and real world experiments, good performances.

  • 34.
    Di Rocco, Maurizio
    et al.
    Roma Tre University.
    Pascucci, Federica
    Roma Tre University.
    Sensor network localization using distributed extended Kalman filter2007Conference paper (Refereed)
  • 35.
    Di Rocco, Maurizio
    et al.
    Roma Tre University.
    Pascucci, Federica
    Roma Tre University.
    Perillo, David
    Roma Tre University.
    Consensus filter for sensor networks localization and tracking2007Conference paper (Refereed)
  • 36.
    Di Rocco, Maurizio
    et al.
    Örebro University, School of Science and Technology.
    Pecora, Federico
    Örebro University, School of Science and Technology.
    Sivakumar, Prasanna Kumar
    Örebro University, School of Science and Technology.
    Saffiotti, Alessandro
    Örebro University, School of Science and Technology.
    Configuration Planning with Multiple Dynamic Goals2013In: Designing intelligent robots: reintegrating AI II. Papers from the AAAI Spring Symposium, AAAI Press, 2013, p. 12-17Conference paper (Refereed)
    Abstract [en]

    We propose an approach to configuration planning for robotic systems in which plans are represented as constraint networks and planning is defined as search in the space of such networks. The approach supports reasoning about time, resources, and information dependencies between actions. In addition, the system can leverage the flexibility of such networks at execution time to support dynamic goal posting and re-planning.

  • 37.
    Di Rocco, Maurizio
    et al.
    Örebro University, School of Science and Technology.
    Reggente, Matteo
    Saffiotti, Alessandro
    Örebro University, School of Science and Technology.
    Gas source localization in indoor environments using multiple inexpensive robots and stigmergy2011In: 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), IEEE, 2011, p. 5007-5014Conference paper (Refereed)
    Abstract [en]

    Environmental monitoring is a rather new field in robotics. One of the main appealing tasks is gas mapping, i.e., the characterization of the chemical properties (concentration, dispersion, etc.) of the air within an environment. Current approaches rely on a robot using standard localization and mapping techniques to fuse gas measures with spatial features. These approaches require sophisticated sensors and/or high computational resources. We propose a minimalistic approach, in which one or multiple low-cost robots exploit the ability to store information in the environment, or “stigmergy”, to effectively compute an artificial potential leading toward the likely location of the gas source, as indicated by a highest gas concentration or fluctuation. The potential is computed and stored directly on an array of RFID tags buried under the floor. Our approach has been validated in extensive experiments performed on real robots in a domestic environment.

  • 38.
    Di Rocco, Maurizio
    et al.
    Roma Tre University, Rome, Italy.
    Ulivi, Giavanni
    An efficient implementation of a particle filter for localization using compass data2010In: 7th IFAC Symposium on Intelligent Autonomous Vehicles 2010, Lecce, Italy / [ed] Giovanni Indiveri, Antonio M. Pascoal, 2010Conference paper (Refereed)
    Abstract [en]

    This paper presents a localization algorithm for a small mobile platform. Taking advantage from modern technology, Saetta, a low cost mobile robot, has been built from scratch. Due to the limited processing capabilities, some ad hoc solutions have been used: the lack of processing resources has been compensated by an efficient implementation of the estimator and by the use of compass measures which ease the computational load. The results show how a careful design allows the implementation of sophisticated algorithms also on small platforms.

  • 39.
    Dimitrov, Dimitar
    et al.
    Örebro University, School of Science and Technology.
    Paolillo, Antonio
    Wieber, Pierre-Brice
    Walking motion generation with online foot position adaptation based on L_1- and L_\inf-norm penalty formulations2010In: IEEE International conference on Robotics and automation (ICRA), IEEE conference proceedings, 2010, p. 3523-3529Conference paper (Refereed)
    Abstract [en]

    The article presents an improved formulation of an existing model predictive control scheme used to generate online "stable" walking motions for a humanoid robot. We introduce: (i) a change of variable that simplifies the optimiza tion problem to be solved; (ii) a simply bounded formulation in the case when the positions of the feet are predetermined; (iii) a formulation allowing foot repositioning (when the system is perturbed) based on ℓ1- and ℓ-norm minimization; (iv) a formulation that accounts for (approximate) double support constraints when foot repositioning occurs.

  • 40.
    Dimitrov, Dimitar
    et al.
    Örebro University, School of Science and Technology.
    Sherikov, Alexander
    Örebro University, School of Science and Technology.
    Wieber, Pierre-Brice
    A sparse model predictive control formulation for walking motion generation2011In: IEEE/RSJ International conference on Intelligent robots and systems (IROS), IEEE, 2011, p. 2292-2299Conference paper (Refereed)
    Abstract [en]

    This article presents a comparison between dense and sparse model predictive control (MPC) formulations, in the context of walking motion generation for humanoid robots. The former formulation leads to smaller, the latter one to larger but more structured optimization problem. We put an accent on the sparse formulation and point out a number of advantages that it presents. In particular, motion generation with variable center of mass (CoM) height, as well as variable discretization of the preview window, come at a negligible additional computational cost. We present a sparse formulation that comprises a diagonal Hessian matrix and has only simple bounds (while still retaining the possibility to generate motions for an omnidirectional walk). Finally, we present the results from a customized code used to solve the underlying quadratic program (QP).

  • 41.
    Dimitrov, Dimitar
    et al.
    Örebro University, School of Science and Technology.
    Wieber, Pierre-Brice
    Stasse, Olivier
    Ferreau, Hans Joachim
    Diedam, Holger
    An optimized linear model predictive control solver2010In: Recent advances in optimization and its applications in engineering / [ed] Moritz Diehl, Francois Glineur, Elias Jarlebring, Wim Michiels, Heidelberg: Springer, 2010, 1, p. 309-318Chapter in book (Refereed)
  • 42.
    Eleonora, Thorén
    Örebro University, School of Science and Technology.
    Packstation: Utredning om lösningar för automatiserad hantering2012Independent thesis Basic level (professional degree), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    The report describes an investigative assignment done for Lantmännen Unibake, Korvbrödsbagarn, where they wanted an automated solution for packaging bags into boxes to replace the manual handling that they have today.

    The method used to find a suitable solution was the PDCA-cycle (Plan-Do-Check-Act), where four different phases are reviewed to get an understanding of the present and the desired solution, investigate available alternatives trough contact with agents for machinery companies, evaluation of the solutions and for last a conclusion and suggestion for continuing the work.

  • 43.
    Fan, Han
    et al.
    Örebro University, School of Science and Technology.
    Arain, Muhammad Asif
    Örebro University, School of Science and Technology.
    Hernandez Bennetts, Victor
    Örebro University, School of Science and Technology.
    Schaffernicht, Erik
    Örebro University, School of Science and Technology.
    Lilienthal, Achim J.
    Örebro University, School of Science and Technology.
    Improving Gas Dispersal Simulation For Mobile Robot Olfaction: Using Robotcreatedoccupancy Maps And Remote Gas Sensors In The Simulation Loop2017In: 2017 ISOCS/IEEE International Symposium on Olfaction andElectronic Nose (ISOEN 2017) Proceedings, IEEE conference proceedings, 2017, article id 17013581Conference paper (Refereed)
    Abstract [en]

    Mobile robot platforms equipped with olfaction systems have been used in many gas sensing applications. However, in-field validation of mobile robot olfaction systems is time consuming, expensive, cumbersome and lacks repeatability. In order to address these issues, simulation tools are used. However, the available mobile robot olfaction simulations lack models for remote gas sensors, and the possibility to import geometrical representations of actual real-world environments in a convenient way. In this paper, we describe extensions to an open-source CFD-based filament gas dispersal simulator. These improvements arrow to use robot-created occupancy maps and offer remote sensing capabilities in the simulation loop. We demonstrate the novel features in an example application: we created a 3D map a complex indoor environment, and performed a gas emission monitoring task with a Tunable Diode Laser Absorption Spectroscopy based remote gas sensor in a simulated version of the environment.

  • 44.
    Fiorini, Flavio
    et al.
    Roma Tre University, Rome, Italy.
    Gasparri, Andrea
    Roma Tre University, Rome, Italy.
    Di Rocco, Maurizio
    Roma Tre University, Rome, Italy.
    Panzieri, Stefano
    Roma Tre University, Rome, Italy.
    A networked transferable belief model approach for distributed data aggregation: dynamic version2010In: 49th IEEE Conference on Decision and Control (CDC), 2010, IEEE conference proceedings, 2010, p. 1237-1242Conference paper (Refereed)
    Abstract [en]

    This paper investigates the data aggregation problem for a multi-agent system. In this framework, agents are assumed to be independent reliable sources which collect data and collaborate to reach a common knowledge. In particular, agents are assumed to dynamically gather data over time, i.e., a dynamic scenario. A protocol for distributed data aggregation which is proved to converge to the basic belief assignment (BBA) given by a centralized aggregation based on the Transferable Belief Model (TBM) is provided.

  • 45.
    Fiorini, Flavio
    et al.
    Roma Tre University, Rome, Italy.
    Gasparri, Andrea
    Roma Tre University, Rome, Italy.
    Di Rocco, Maurizio
    Roma Tre University, Rome, Italy.
    Panzieri, Stefano
    Roma Tre University, Rome, Italy.
    A networked transferable belief model approach for distributed data aggregation: static version2010In: 49th IEEE Conference on Decision and Control (CDC), 2010, IEEE conference proceedings, 2010, p. 1229-1236Conference paper (Refereed)
    Abstract [en]

    In this paper the data aggregation problem for a multi-agent system is investigated. In this framework, agents are assumed to be independent reliable sources which collect data and collaborate to reach a common knowledge. In particular, each agent is supposed to provide an observation which does not change over time, i.e., static scenario. A protocol for distributed data aggregation which is proved to converge to the basic belief assignment (BBA) given by a centralized aggregation based on the Transferable Belief Model (TBM) is provided.

  • 46.
    Franchi, Antonio
    et al.
    La Sapienza University, Rome, Italy.
    Stegagno, Paolo
    La Sapienza University, Rome, Italy.
    Di Rocco, Maurizio
    Roma Tre University, Rome, Italy.
    Oriolo, Giuseppe
    La Sapienza University, Rome, Italy.
    Distributed target localization and encirclement with a multi robot system2010In: 7th IFAC Symposium on Intelligent Autonomous Vehicles 2010, Lecce, Italy / [ed] Giovanni Indiveri, Antonio M. Pascoal, 2010Conference paper (Refereed)
    Abstract [en]

    This paper presents a control scheme for localizing and encircling a target using a multi-robot system. The task is achieved in a distributed way, in that each robot only uses local information gathered by on-board relative-position sensors assumed to be noisy, anisotropic, and unable to detect the identity of the measured object. Communication between the robots is provided by limited-range transceivers. Experimental results with stationary and moving targets support the theoretical analysis.

  • 47.
    Frese, Udo
    et al.
    University of Bremen.
    Larsson, Per
    NamaTec AB.
    Duckett, Tom
    Örebro University, Department of Technology.
    A multilevel relaxation algorithm for simultaneous localisation and mapping2005In: IEEE Transactions on robotics, ISSN 1552-3098, E-ISSN 1941-0468, Vol. 21, no 2, p. 196-207Article in journal (Refereed)
    Abstract [en]

    This paper addresses the problem of simultaneous localisation and mapping (SLAM) by a mobile robot. An incremental SLAM algorithm is introduced that is derived from multigrid methods used for solving partial differential equations. The approach improves on the performance of previous relaxation methods for robot mapping because it optimizes the map at multiple levels of resolution. The resulting algorithm has an update time that is linear in the number of estimated features for typical indoor environments, even when closing very large loops, and offers advantages in handling non-linearities compared to other SLAM algorithms. Experimental comparisons with alternative algorithms using two well-known data sets and mapping results on a real robot are also presented

  • 48. Galindo, Cipriano
    et al.
    González, Javier
    Fernández-Madrigal, Juan-Antonio
    Saffiotti, Alessandro
    Örebro University, School of Science and Technology.
    Robots that change their world: inferring goals from semantic knowledge2011In: Proceedings of the 5th European Conference on Mobile Robots, ECMR 2011 / [ed] Achim J. Lilienthal, Tom Duckett, 2011, p. 1-6Conference paper (Refereed)
  • 49.
    Galindo, Cipriano
    et al.
    University of Malaga, Malaga, Spain.
    Saffiotti, Alessandro
    Örebro University, School of Science and Technology.
    Inferring robot goals from violations of semantic knowledge2013In: Robotics and Autonomous Systems, ISSN 0921-8890, E-ISSN 1872-793X, Vol. 61, no 10, p. 1131-1143Article in journal (Refereed)
    Abstract [en]

    A growing body of literature shows that endowing a mobile robot with semantic knowledge and with the ability to reason from this knowledge can greatly increase its capabilities. In this paper, we present a novel use of semantic knowledge, to encode information about how things should be, i.e. norms, and to enable the robot to infer deviations from these norms in order to generate goals to correct these deviations. For instance, if a robot has semantic knowledge that perishable items must be kept in a refrigerator, and it observes a bottle of milk on a table, this robot will generate the goal to bring that bottle into a refrigerator. The key move is to properly encode norms in an ontology so that each norm violation results in a detectable inconsistency. A goal is then generated to bring the world back in a consistent state, and a planner is used to transform this goal into actions. Our approach provides a mobile robot with a limited form of goal autonomy: the ability to derive its own goals to pursue generic aims. We illustrate our approach in a full mobile robot system that integrates a semantic map, a knowledge representation and reasoning system, a task planner, and standard perception and navigation routines. (C) 2013 Elsevier B.V. All rights reserved.

  • 50.
    Galindo, Cipriano
    et al.
    University of Malaga, Malaga, Spain.
    Saffiotti, Alessandro
    Örebro University, School of Science and Technology.
    Semantic norms for mobile robots: when the end does not justify the means2012Conference paper (Refereed)
    Abstract [en]

    This paper deals with the use of semantic knowledge to improve the intelligence and autonomous behavior of a mobile robot. A robot can exploit the semantics of its environment to infer new, implicit information. Another interesting possibility is to use semantics for detecting deviations between the real world and what is supposed to be ``normal''. For instance, normative semantic knowledge may state that towels should stay in the bathroom. If a robot detects a towel in the kitchen, it can react and decide to solve this inconsistency by bringing it to the bathroom. However not all ways to solve an inconsistency are acceptable: for instance, if the robot put the towel temporarily on a dirty sink in order to re-grasp it with the other arm, it would violate another norm -- namely, that towels should always stay on a clean surface. In this work we present an algorithm that detects and recovers from norm violations, according to a semantic representation of norms, and ensures the normative acceptability of the robot actions throughout execution.

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