Browsing by Author "Hartmann, V. N."

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    Learning robotic manipulation of natural materials with variable properties for construction tasks
    (Institute of Electrical and Electronics Engineers, 2022-03-15) Kalousdian, N. K.; Lochnicki, G.; Hartmann, V. N.; Leder, S.; Oğuz, Özgür S.; Menges, A.; Toussaint, M.
    The introduction of robotics and machine learning to architectural construction is leading to more efficient construction practices. So far, robotic construction has largely been implemented on standardized materials, conducting simple, predictable, and repetitive tasks. We present a novel mobile robotic system and corresponding learning approach that takes a step towards assembly of natural materials with anisotropic mechanical properties for more sustainable architectural construction. Through experiments both in simulation and in the real world, we demonstrate a dynamically adjusted curriculum and randomization approach for the problem of learning manipulation tasks involving materials with biological variability, namely bamboo. Using our approach, robots are able to transport bamboo bundles and reach to goal-positions during the assembly of bamboo structures.
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    Leveraging building material as part of the in-plane robotic kinematic system for collective construction
    (Advanced Science, 2022-06-24) Leder, S.; Kim, H.; Oguz, Ozgur Salih; Kalousdian, N. K.; Hartmann, V. N.; Menges, A.; Toussaint, M.; Sitti, M.
    Although collective robotic construction systems are beginning to showcasehow multi-robot systems can contribute to building construction by efficientlybuilding low-cost, sustainable structures, the majority of research utilizesnon-structural or highly customized materials. A modular collective roboticconstruction system based on a robotic actuator, which leverages timberstruts for the assembly of architectural artifacts as well as part of the robotbody for locomotion is presented. The system is co-designed for in-planeassembly from an architectural, robotic, and computer science perspective inorder to integrate the various hardware and software constraints into a singleworkflow. The system is tested using five representative physical scenarios.These proof-of-concept demonstrations showcase three tasks required forconstruction assembly: the ability of the system to locomote, dynamicallychange the topology of connecting robotic actuators and timber struts, andcollaborate to transport timber struts. As such, the groundwork for a futureautonomous collective robotic construction system that could addresscollective construction assembly and even further increase the flexibility ofon-site construction robots through its modularity is laid.