Collective Motion Planning for a Group of Robots Using Intermittent Diffusion

Christina Frederick; Magnus Egerstedt; Haomin Zhou

doi:10.1007/s10915-021-01700-y

Collective Motion Planning for a Group of Robots Using Intermittent Diffusion

Christina Frederick, Magnus Egerstedt, Haomin Zhou

Mathematical Sciences

Research output: Contribution to journal › Article › peer-review

5 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 language	English (US)
Article number	13
Journal	Journal of Scientific Computing
Volume	90
Issue number	1
DOIs	https://doi.org/10.1007/s10915-021-01700-y
State	Published - Jan 2022

All Science Journal Classification (ASJC) codes

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

Keywords

Intermittent diffusion
Multi-agent systems
Optimal transport
Path planning

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10.1007/s10915-021-01700-y

Cite this

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title = "Collective Motion Planning for a Group of Robots Using Intermittent Diffusion",

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.",

keywords = "Intermittent diffusion, Multi-agent systems, Optimal transport, Path planning",

author = "Christina Frederick and Magnus Egerstedt and Haomin Zhou",

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AU - Egerstedt, Magnus

AU - Zhou, Haomin

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N2 - 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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KW - Multi-agent systems

KW - Optimal transport

KW - Path planning

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Collective Motion Planning for a Group of Robots Using Intermittent Diffusion

Abstract

All Science Journal Classification (ASJC) codes

Keywords

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