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  • 1.
    Baerveldt, Albert-Jan
    Högskolan i Halmstad, Sektionen för Informationsvetenskap, Data– och Elektroteknik (IDE).
    Guest editorial: Agricultural robotics2002Ingår i: Autonomous Robots, ISSN 0929-5593, E-ISSN 1573-7527, Vol. 13, nr 1, s. 5-7Artikel i tidskrift (Refereegranskat)
  • 2.
    Brooks, Christopher A.
    et al.
    Tau Beta Pi, United States.
    Iagnemma, Karl
    MIT, USA.
    Dubowsky, Steven
    MIT, USA.
    Visual wheel sinkage measurement for planetary rover mobility characterization2006Ingår i: Autonomous Robots, ISSN 0929-5593, E-ISSN 1573-7527, Vol. 21, nr 1, s. 55-64Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Wheel sinkage is an important indicator of mobile robot mobility in natural outdoor terrains. This paper presents a vision-based method to measure the sinkage of a rigid robot wheel in rigid or deformable terrain. The method is based on detecting the difference in intensity between the wheel rim and the terrain. The method uses a single grayscale camera and is computationally efficient, making it suitable for systems with limited computational resources such as planetary rovers. Experimental results under various terrain and lighting conditions demonstrate the effectiveness and robustness of the algorithm.

  • 3.
    Gholami Shahbandi, Saeed
    et al.
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Magnusson, Martin
    Örebro University, Örebro, Sweden.
    2D Map Alignment With Region Decomposition2019Ingår i: Autonomous Robots, ISSN 0929-5593, E-ISSN 1573-7527, Vol. 43, nr 5, s. 1117-1136Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    In many applications of autonomous mobile robots the following problem is encountered. Two maps of the same environment are available, one a prior map and the other a sensor map built by the robot. To benefit from all available information in both maps, the robot must find the correct alignment between the two maps. There exist many approaches to address this challenge, however, most of the previous methods rely on assumptions such as similar modalities of the maps, same scale, or existence of an initial guess for the alignment. In this work we propose a decomposition-based method for 2D spatial map alignment which does not rely on those assumptions. Our proposed method is validated and compared with other approaches, including generic data association approaches and map alignment algorithms. Real world examples of four different environments with thirty six sensor maps and four layout maps are used for this analysis. The maps, along with an implementation of the method, are made publicly available online. © 2018, The Author(s).

  • 4.
    Iagnemma, Karl
    et al.
    Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, USA.
    Ward, Chris C.
    Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, USA.
    Classification-based wheel slip detection and detector fusion for mobile robots on outdoor terrain2009Ingår i: Autonomous Robots, ISSN 0929-5593, E-ISSN 1573-7527, Vol. 26, nr 1, s. 33-46Artikel i tidskrift (Refereegranskat)
  • 5.
    Kruusmaa, Maarja
    Högskolan i Halmstad, Sektionen för Informationsvetenskap, Data– och Elektroteknik (IDE).
    Global Navigation in Dynamic Environments Using Case-Based Reasoning2004Ingår i: Autonomous Robots, ISSN 0929-5593, E-ISSN 1573-7527, Vol. 14, nr 1, s. 71-91Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    This paper presents a global navigation strategy for autonomous mobile robots in large-scale uncertain environments. The aim of this approach is to minimize collision risk and time delays by adapting to the changes in a dynamic environment. The issue of obstacle avoidance is addressed on the global level. It focuses on a navigation strategy that prevents the robot from facing the situations where it has to avoid obstacles. To model the partially known environment, a grid-based map is used. A modified wave-transform algorithm is described that finds several alternative paths from the start to the goal. Case-based reasoning is used to learn from past experiences and to adapt to the changes in the environment. Learning and adaptation by means of case-based reasoning permits the robot to choose routes that are less risky to follow and lead faster to the goal. The experimental results demonstrate that using case-based reasoning considerably increases the performance of the robot in a difficult uncertain environment. The robot learns to take actions that are more predictable, minimize collision risk and traversal time as well as traveled distances.

  • 6.
    Magnenat, Stéphane
    et al.
    ETH Zentrum, Zürich, Switzerland.
    Philippsen, Roland
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), Laboratoriet för intelligenta system.
    Mondada, Francesco
    École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.
    Autonomous construction using scarce resources in unknown environments: Ingredients for an intelligent robotic interaction with the physical world2012Ingår i: Autonomous Robots, ISSN 0929-5593, E-ISSN 1573-7527, Vol. 33, nr 4, s. 476-485Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    The goal of creating machines that autonomously perform useful work in a safe, robust and intelligent manner continues to motivate robotics research.Achieving this autonomy requires capabilities for understanding the environment, physically interacting with it, predicting the outcomes of actions and reasoning with this knowledge.Such intelligent physical interaction was at the centre of early robotic investigations and remains an open topic.

    In this paper, we build on the fruit of decades of research to explore further this question in the context of autonomous construction in unknown environments with scarce resources.Our scenario involves a miniature mobile robot that autonomously maps an environment and uses cubes to bridge ditches and build vertical structures according to high-level goals given by a human.

    Based on a "real but contrived" experimental design, our results encompass practical insights for future applications that also need to integrate complex behaviours under hardware constraints, and shed light on the broader question of the capabilities required for intelligent physical interaction with the real world.

  • 7.
    Sentis, Luis
    et al.
    The University of Texas at Austin, Austin, TX, USA.
    Petersen, Josh
    The University of Texas at Austin, Austin, TX, USA.
    Philippsen, Roland
    Högskolan i Halmstad, Sektionen för Informationsvetenskap, Data– och Elektroteknik (IDE), Halmstad Embedded and Intelligent Systems Research (EIS), Intelligenta system (IS-lab).
    Implementation and stability analysis of prioritized whole-body compliant controllers on a wheeled humanoid robot in uneven terrains2013Ingår i: Autonomous Robots, ISSN 0929-5593, E-ISSN 1573-7527, Vol. 35, nr 4, s. 301-319Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    In this work, we implement the floating base prioritized whole-body compliant control framework described in Sentis et al. (IEEE Transactions on Robotics 26(3):483–501, 2010) on a wheeled humanoid robot maneuvering in sloped terrains. We then test it for a variety of compliant whole-body behaviors including balance and kinesthetic mobility on irregular terrain, and Cartesian hand position tracking using the co-actuated (i.e. two joints are simultaneously actuated with one motor) robot’s upper body. The implementation serves as a hardware proof for a variety of whole-body control concepts that had previously been developed and tested in simulation. First, behaviors of two and three priority tasks are implemented and successfully executed on the humanoid hardware. In particular, first and second priority tasks are linearized in the task space through model feedback and then controlled through task accelerations. Postures, on the other hand, are shown to be asymptotically stable when using prioritized whole-body control structures and then successfully tested in the real hardware. To cope with irregular terrains, the base is modeled as a six degree of freedom floating system and the wheels are characterized through contact and rolling constraints. Finally, center of mass balance capabilities using whole-body compliant control and kinesthetic mobility are implemented and tested in the humanoid hardware to climb terrains with various slopes.

  • 8.
    Åstrand, Björn
    et al.
    Högskolan i Halmstad, Sektionen för Informationsvetenskap, Data– och Elektroteknik (IDE), Halmstad Embedded and Intelligent Systems Research (EIS).
    Baerveldt, Albert-Jan
    Högskolan i Halmstad.
    An agricultural mobile robot with vision-based perception for mechanical weed control2002Ingår i: Autonomous Robots, ISSN 0929-5593, E-ISSN 1573-7527, Vol. 13, nr 1, s. 21-35Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    This paper presents an autonomous agricultural mobile robot for mechanical weed control in outdoor environments. The robot employs two vision systems: one gray-level vision system that is able to recognize the row structure formed by the crops and to guide the robot along the rows and a second, color-based vision system that is able to identify a single crop among weed plants. This vision system controls a weeding-tool that removes the weed within the row of crops. The row-recognition system is based on a novel algorithm and has been tested extensively in outdoor field tests and proven to be able to guide the robot with an accuracy of 2 cm. It has been shown that color vision is feasible for single plant identification, i.e., discriminating between crops and weeds. The system as a whole has been verified, showing that the subsystems are able to work together effectively. A first trial in a greenhouse showed that the robot is able to manage weed control within a row of crops.

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