Construction Task Allocation Through the Collective Perception of a Dynamic Environment

Yara Khaluf*, Michael Allwright, Ilja Rausch, Pieter Simoens, Marco Dorigo

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference paperAcademicpeer-review

5 Citations (Scopus)


Building structures is a remarkable collective process but its automation remains an open challenge. Robot swarms provide a promising solution to this challenge. However, collective construction involves a number of difficulties regarding efficient robots allocation to the different activities, particularly if the goal is to reach an optimal construction rate. In this paper, we study an abstract construction scenario, where a swarm of robots is engaged in a collective perception process to estimate the density of building blocks around a construction site. The goal of this perception process is to maintain a minimum density of blocks available to the robots for construction. To maintain this density, the allocation of robots to the foraging task needs to be adjusted such that enough blocks are retrieved. Our results show a robust collective perception that enables the swarm to maintain a minimum block density under different rates of construction and foraging. Our approach leads the system to stabilize around a state in which the robots allocation allows the swarm to maintain a tile density that is close to or above the target minimum.

Original languageEnglish
Title of host publicationSwarm Intelligence - 12th International Conference, ANTS 2020, Proceedings
EditorsMarco Dorigo, Thomas Stützle, Maria J. Blesa, Christian Blum, Heiko Hamann, Mary Katherine Heinrich, Volker Strobel
Place of PublicationCham
Number of pages14
ISBN (Print)9783030603755
Publication statusPublished - 2020
Externally publishedYes
Event12th International Conference on Swarm Intelligence, ANTS 2020 - Barcelona, Spain
Duration: 26 Oct 202028 Oct 2020

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12421 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference12th International Conference on Swarm Intelligence, ANTS 2020


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