Bubble-raft inspired shape-assembly in flying robot swarm for uniform formation and obstacle traversal

Natural swarms can move cohesively while continuously reshaping their spatial shape, yet reproducing this behavior with large flying robot swarms in obstacle environments remains difficult, especially in achieving uniformity and safety. Here, we present a distributed 3D shape-assembly controller for flying robot swarms that forms arbitrary target shapes with uniform coverage and safe inter-robot distance. Inspired by bubble-rafts, each robot is associated with a non-overlapping region inside the target shape and updates its velocity by considering region exploration, region balancing and distance fine-tuning. The proposed region-based shape-assembly method is able to drive the swarm toward uniform formations and enable fast shape transformation, as well as resilience to robot joining and failure. For navigation, we design a lightweight velocity-obstacle mechanism that adjusts the nominal shape-assembly velocity to collision-free commands with minimal formation disruption. We validate the proposed methods in extensive simulations and real-world swarm experiments, demonstrating efficient formation of complex 3D shapes, robust maintenance of safety distances, and reliable obstacle traversal.

Authors

Institutions

Publication Details

Journal
Communications Engineering
Published
2026-07-02
DOI
https://doi.org/10.1038/s44172-026-00715-3
Primary Topic
Distributed Control Multi-Agent Systems
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Bubble-raft inspired shape-assembly in flying robot swarm for uniform formation and obstacle traversal

Hanxun Li, Jinshu Su, Biao Han, Zhiqiang Li et al.
Communications Engineering
Distributed Control Multi-Agent Systems
article

Bubble-raft inspired shape-assembly in flying robot swarm for uniform formation and obstacle traversal

Hanxun Li, Jinshu Su, Biao Han, Zhiqiang Li, Yining Zhao, Tingyu Chen
article en

Abstract

Natural swarms can move cohesively while continuously reshaping their spatial shape, yet reproducing this behavior with large flying robot swarms in obstacle environments remains difficult, especially in achieving uniformity and safety. Here, we present a distributed 3D shape-assembly controller for flying robot swarms that forms arbitrary target shapes with uniform coverage and safe inter-robot distance. Inspired by bubble-rafts, each robot is associated with a non-overlapping region inside the target shape and updates its velocity by considering region exploration, region balancing and distance fine-tuning. The proposed region-based shape-assembly method is able to drive the swarm toward uniform formations and enable fast shape transformation, as well as resilience to robot joining and failure. For navigation, we design a lightweight velocity-obstacle mechanism that adjusts the nominal shape-assembly velocity to collision-free commands with minimal formation disruption. We validate the proposed methods in extensive simulations and real-world swarm experiments, demonstrating efficient formation of complex 3D shapes, robust maintenance of safety distances, and reliable obstacle traversal.

Communications Engineering
National University of Defense Technology (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 6%
Distributed Control Multi-Agent Systems
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Bubble-raft inspired shape-assembly in flying robot swarm for uniform formation and obstacle traversal — Hanxun Li, Jinshu Su, et al. · Communications Engineering (2026) | TGRS Research Map | TGRS