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Collective Motion Planning for a Group of Robots Using Intermittent Diffusion

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Abstract

In this work we establish a simple yet effective strategy, based on intermittent diffusion, for enabling a group of robots to accomplish complex tasks, shape formation and assembly. We demonstrate the feasibility of this approach and rigorously prove collision avoidance and convergence properties of the proposed algorithms.

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Data Availability Statement

The datasets generated during and/or analysed during the current study areavailable from the corresponding author on reasonable request.

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Funding

This research was supported by NSF Grants DMS-1830225, DMS-1620345, DMS-1720306, ONR N00014-21-1-2856, and ONR N00014-18-1-2852.

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Authors and Affiliations

  1. Department of Mathematical Sciences, New Jersey Institute of Technology, Newark, New Jersey, 10702, USA

    Christina Frederick

  2. Department of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, 30332, USA

    Magnus Egerstedt

  3. Department of Mathematics, Georgia Institute of Technology, Atlanta, GA, 30332, USA

    Haomin Zhou

Authors
  1. Christina Frederick
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  2. Magnus Egerstedt
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  3. Haomin Zhou
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Correspondence to Christina Frederick.

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The code generated during the current study is available from the corresponding author on reasonable request.

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This work was partially supported by grants NSF DMS-1830225, DMS-1620345, DMS-1720306, ONR N00014-21-1-2856, and ONR N00014-18-1-2852.

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Frederick, C., Egerstedt, M. & Zhou, H. Collective Motion Planning for a Group of Robots Using Intermittent Diffusion. J Sci Comput 90, 13 (2022). https://doi.org/10.1007/s10915-021-01700-y

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