abstract

Heuristic Evaluation of Swarm Metrics' Effectiveness

Authors:

Matthew D. Manning,

Caroline E. Harriott,

Sean T. Hayes,

Julie A. Adams, and

Adriane E. SeiffertAuthors Info & Claims

HRI'15 Extended Abstracts: Proceedings of the Tenth Annual ACM/IEEE International Conference on Human-Robot Interaction Extended Abstracts

March 2015

Pages 17 - 18

https://doi.org/10.1145/2701973.2702046

Published: 02 March 2015 Publication History

Get Access

Abstract

Typical visualizations of robot swarms (greater than 50 entities) display each individual entity; however, it is immensely difficult to maintain accurate position information for each member in real-world situations with limited communications. Generally, it will be difficult for humans to maintain an awareness of all individual entities. Further, the swarm's tasks may impact the desired visualization. Thus, an open question is how best to visualize a swarm given various swarm tasks. This paper presents a heuristic evaluation that analyzes the application of swarm metrics to different swarm visualizations and tasks. A brief overview of the visualizations is provided, along with a description of the heuristic metrics and the analysis.

References

[1]

Cavagna, A., Duarte Queirós, S. M., Giardina, I., Stafanini, F., and Viale, M. 2013. Diffusion of individual birds in starling flocks. Proceedings of the Royal Society: Biological Sciences, 280(1756): 1--9.

Crossref

Google Scholar

[2]

Couzin, I. D., Krause, J., Franks, N. R., and Levin, S. A. 2005. Effective leadership and decision-making in animal groups on the move. Nature: 433: 513--516.

Crossref

Google Scholar

[3]

Goodrich, M. A., Sujit, P. B., Kerman, S., Pendleton, B., and Pinto, J. 2011. Enabling human interaction with bio-inspired robot teams: Topologies, leaders, predators and stakeholders. BYU-HCMI Technical Report 2011--1.

Google Scholar

[4]

Haas, E., Fields, M., Hill, S., and Stachowiak, C. 2009. Extreme Scalability: Designing Interfaces and Algorithms for Soldier-Robotic Swarm Interaction (No. ARL-TR-4800). ARMY Research Lab, Aberdeen Proving Ground, Maryland.

Google Scholar

[5]

Harriott, C. E., Seiffert, A. E., Hayes, S. T., and Adams, J. A. 2014. Biologically-Inspired Human-Swarm Interaction Metrics. Proceedings of the Human Factors and Ergonomics Society 58th Annual Meeting, pp. 1471--1475.

Google Scholar

[6]

Leca, J-B., Gunst, N., Thierry, B., and Petit, O. 2003. Distributed leadership in semifree-ranging white-faced capuchin monkeys. Animal Behavior, 66: 1045--1052.

Crossref

Google Scholar

[7]

Young, G. F., Scardovi, L., Cavagna, A., Giardina, I., and Leonard, N. 2013. Starling Flock Networks Manage Uncertainty in Consensus at Low Cost. PLOS Computational Biology, 9(1).

Google Scholar

Cited By

View all

Yang SSamarasinghe DArukgoda AAbpeikar SLakshika EBarlow M(2023)Automatic Recognition of Collective Emergent Behaviors Using Behavioral MetricsIEEE Access10.1109/ACCESS.2023.330468211(89077-89092)Online publication date: 2023
https://doi.org/10.1109/ACCESS.2023.3304682
Capiola AJohnson DHamdan ILyons JFox E(2023)Detecting Swarm Degradation: Measuring Human and Machine PerformanceVirtual, Augmented and Mixed Reality10.1007/978-3-031-35634-6_23(325-343)Online publication date: 9-Jul-2023
https://doi.org/10.1007/978-3-031-35634-6_23
Alharthi KAbdallah ZHauert S(2022)Automatic Extraction of Understandable Controllers from Video Observations of Swarm BehaviorsSwarm Intelligence10.1007/978-3-031-20176-9_4(41-53)Online publication date: 2-Nov-2022
https://dl.acm.org/doi/10.1007/978-3-031-20176-9_4
Show More Cited By

Index Terms

Recommendations

Towards a metrics-based framework for assessing comprehension of software visualization systems
Proceedings of the 2007 conference on Human interface: Part I

Despite the burgeoning interest shown in visualizations by diverse disciplines, there yet remains the unresolved question concerning comprehension. Is the concept that is being communicated through the visual easily grasped and clearly interpreted? ...
Read More
A heuristic particle swarm optimization
GECCO '07: Proceedings of the 9th annual conference on Genetic and evolutionary computation

A heuristic version of the particle swarm optimization (PSO) is introduced in this paper. In this new method called "The heuristic particle swarm optimization(HPSO)", we use heuristics to choose the next particle to update its velocity and position. By ...
Read More
Are Slice-Based Cohesion Metrics Actually Useful in Effort-Aware Post-Release Fault-Proneness Prediction? An Empirical Study
Background. Slice-based cohesion metrics leverage program slices with respect to the output variables of a module to quantify the strength of functional relatedness of the elements within the module. Although slice-based cohesion metrics have been ...
Read More

Comments

Information & Contributors

Information

Published In

HRI'15 Extended Abstracts: Proceedings of the Tenth Annual ACM/IEEE International Conference on Human-Robot Interaction Extended Abstracts

March 2015

336 pages

ISBN:9781450333184

DOI:10.1145/2701973

General Chairs:
Julie A. Adams
Vanderbilt University, USA
,
William Smart
Oregon State University, USA
,
Program Chairs:
Bilge Mutlu
University of Wisconsin-Madison, USA
,
Leila Takayama
Google[x], USA

Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 02 March 2015

Check for updates

Author Tags

Qualifiers

Abstract

Funding Sources

Office of Naval Research

Conference

HRI '15

Sponsor:

HRI '15: ACM/IEEE International Conference on Human-Robot Interaction

March 2 - 5, 2015

Oregon, Portland, USA

Acceptance Rates

HRI'15 Extended Abstracts Paper Acceptance Rate 92 of 102 submissions, 90%;

Overall Acceptance Rate 192 of 519 submissions, 37%

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

13
Total Citations
View Citations
231
Total Downloads

Downloads (Last 12 months)18
Downloads (Last 6 weeks)3

Other Metrics

View Author Metrics

Citations

Cited By

View all

Yang SSamarasinghe DArukgoda AAbpeikar SLakshika EBarlow M(2023)Automatic Recognition of Collective Emergent Behaviors Using Behavioral MetricsIEEE Access10.1109/ACCESS.2023.330468211(89077-89092)Online publication date: 2023
https://doi.org/10.1109/ACCESS.2023.3304682
Capiola AJohnson DHamdan ILyons JFox E(2023)Detecting Swarm Degradation: Measuring Human and Machine PerformanceVirtual, Augmented and Mixed Reality10.1007/978-3-031-35634-6_23(325-343)Online publication date: 9-Jul-2023
https://doi.org/10.1007/978-3-031-35634-6_23
Alharthi KAbdallah ZHauert S(2022)Automatic Extraction of Understandable Controllers from Video Observations of Swarm BehaviorsSwarm Intelligence10.1007/978-3-031-20176-9_4(41-53)Online publication date: 2-Nov-2022
https://dl.acm.org/doi/10.1007/978-3-031-20176-9_4
Miller CAdams JClark SKane SRoundtree KWalker P(2021)Human Factors Issues and Challenges In Research on ‘Many- Agent’ Control ApplicationsProceedings of the Human Factors and Ergonomics Society Annual Meeting10.1177/107118132064107464:1(324-328)Online publication date: 9-Feb-2021
https://doi.org/10.1177/1071181320641074
Roundtree KCody JLeaf JDemirel HAdams J(2021)Human-collective visualization transparencySwarm Intelligence10.1007/s11721-021-00194-615:3(237-286)Online publication date: 3-Jun-2021
https://doi.org/10.1007/s11721-021-00194-6
Damacharla PDhakal PBandreddi JJavaid AGallimore JElkin CDevabhaktuni V(2020)Novel Human-in-the-Loop (HIL) Simulation Method to Study Synthetic Agents and Standardize Human–Machine Teams (HMT)Applied Sciences10.3390/app1023839010:23(8390)Online publication date: 25-Nov-2020
https://doi.org/10.3390/app10238390
Roundtree KManning MAdams J(2018)Analysis of Human-Swarm VisualizationsProceedings of the Human Factors and Ergonomics Society Annual Meeting10.1177/154193121862106662:1(287-291)Online publication date: 25-Sep-2018
https://doi.org/10.1177/1541931218621066
Adams JChen JGoodrich MKanda TŜabanović SHoffman GTapus A(2018)Swarm TransparencyCompanion of the 2018 ACM/IEEE International Conference on Human-Robot Interaction10.1145/3173386.3177008(45-46)Online publication date: 1-Mar-2018
https://dl.acm.org/doi/10.1145/3173386.3177008
Damacharla PJavaid AGallimore JDevabhaktuni V(2018)Common Metrics to Benchmark Human-Machine Teams (HMT): A ReviewIEEE Access10.1109/ACCESS.2018.28535606(38637-38655)Online publication date: 2018
https://doi.org/10.1109/ACCESS.2018.2853560
Ali TNasr EGheith M(2017)CrowdSWD: A Novel Framework for Crowdsourcing Software Development Inspired by the Concept of Biological MetaphorSoftware Project Management for Distributed Computing10.1007/978-3-319-54325-3_8(171-208)Online publication date: 5-Apr-2017
https://doi.org/10.1007/978-3-319-54325-3_8
Show More Cited By

View Options

Get Access

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Cited By

Index Terms

Recommendations

Towards a metrics-based framework for assessing comprehension of software visualization systems

A heuristic particle swarm optimization

Are Slice-Based Cohesion Metrics Actually Useful in Effort-Aware Post-Release Fault-Proneness Prediction? An Empirical Study