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Robotic additive construction of bar structures: unified sequence and motion planning

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Abstract

Additive robotic construction of building-scale discrete bar structures, such as trusses and space frames, is increasingly attractive due to the potential improvements in efficiency, safety, and design possibilities. However, programming complex robots, such as manipulators with seven degrees of freedom, to successfully complete construction tasks can be tedious, challenging, or impossible for a human to do manually. Namely, the structure must be constructed in a sequence that preserves structural properties, such as stiffness, at each step. At the same time, this sequence must allow for the robot to precisely manipulate elements within the in-progress structure while respecting geometric constraints that, for example, ensure the robot does not collide with what it has built. In this work, we present an automated and newly generalized planning approach for jointly finding a construction sequence and robot motion plan for additive construction that satisfies these requirements. Our approach can be applied in a variety of additive construction processes, and we demonstrate it specifically on spatial extrusion and discrete bar assembly in this paper. We demonstrate the effectiveness of our approach on several simulated and real-world extrusion and assembly tasks, including a human-scale physical prototype, for which our algorithm is deployed for the first time to plan the assembly of a complicated double tangent bar system design.

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Code availability

The code and data used for the computational experiments are available at https://github.com/yijiangh/coop_assembly.

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Funding

Caelan Garrett acknowledges the support from NSF Grants 1420316, 1523767 and 1723381, from AFOSR FA9550-17-1-0165, from ONR Grant N00014-14-1-0486, and an NSF GRFP fellow-ship with primary award number 1122374. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the sponsors.

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Authors and Affiliations

  1. Building Technology Program, Department of Architecture, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA

    Yijiang Huang & Caitlin T. Mueller

  2. Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA

    Caelan R. Garrett

  3. CREATE Laboratory, School of Architecture, Princeton University, Princeton, NJ, 08544, USA

    Ian Ting & Stefana Parascho

Authors
  1. Yijiang Huang
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  2. Caelan R. Garrett
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  3. Ian Ting
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  4. Stefana Parascho
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  5. Caitlin T. Mueller
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Correspondence to Yijiang Huang.

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Huang, Y., Garrett, C.R., Ting, I. et al. Robotic additive construction of bar structures: unified sequence and motion planning. Constr Robot 5, 115–130 (2021). https://doi.org/10.1007/s41693-021-00062-z

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