Hyper-heuristic online learning for self-assembling swarm robots

Shuang Yu, Aldeida Aleti, Jan Carlo Barca, Andy Song

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

2 Citations (Scopus)


A robot swarm is a solution for difficult and large scale tasks. However, controlling and coordinating a swarm of robots is challenging, because of the complexity and uncertainty of the environment where manual programming of robot behaviours is often impractical. In this study we propose a hyper-heuristic methodology for swarm robots. It allows robots to create suitable actions based on a set of low-level heuristics, where each heuristic is a behavioural element. With online learning, the robot behaviours can be improved during execution by autonomous heuristic adjustment. The proposed hyper-heuristic framework is applied to surface cleaning tasks on buildings where multiple separate surfaces exist and complete surface information is difficult to obtain. Under this scenario, the robot swarm not only needs to clean the surfaces efficiently by distributing the robots, but also to move across surfaces by self-assembling into a bridge structure. Experimental results showed the effectiveness of the hyper-heuristic framework; the same group of robots was able to autonomously deal with multiple surfaces of different layouts. Their behaviours can improve over time because of the online learning mechanism.

Original languageEnglish
Title of host publicationComputational Science – ICCS 2018
Subtitle of host publication18th International Conference Wuxi, China, June 11–13, 2018 Proceedings, Part I
EditorsYong Shi, Haohuan Fu, Yingjie Tian, Valeria V. Krzhizhanovskaya, Michael Harold Lees, Jack Dongarra, Peter M. A. Sloot
Place of PublicationCham Switzerland
Number of pages14
ISBN (Electronic)9783319936987
ISBN (Print)9783319936970
Publication statusPublished - 2018
EventInternational Conference on Computational Science 2018 - Wuxi, China
Duration: 11 Jun 201813 Jun 2018
Conference number: 18th
https://link-springer-com.ezproxy.lib.monash.edu.au/book/10.1007/978-3-319-93698-7 (Proceedings)

Publication series

NameLecture Notes in Computer Science
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


ConferenceInternational Conference on Computational Science 2018
Abbreviated titleICCS 2018
Internet address


  • Hyper-heuristics
  • Online learning
  • Robotic behaviors
  • Robotic surface cleaner
  • Self-assembling robots
  • Swarm robots

Cite this