Collective Motion Planning for a Group of Robots Using Intermittent Diffusion

Christina Frederick, Magnus Egerstedt, Haomin Zhou

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

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.

Original languageEnglish (US)
Article number13
JournalJournal of Scientific Computing
Volume90
Issue number1
DOIs
StatePublished - Jan 2022

All Science Journal Classification (ASJC) codes

  • Software
  • General Engineering
  • Computational Mathematics
  • Theoretical Computer Science
  • Applied Mathematics
  • Numerical Analysis
  • Computational Theory and Mathematics

Keywords

  • Intermittent diffusion
  • Multi-agent systems
  • Optimal transport
  • Path planning

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