Collective expression: how robotic swarms convey information with group motion
When faced with the need of implementing a decentralized behavior for a group of collaborating robots, strategies inspired from swarm intelligence often avoid considering the human operator, granting the swarm with full autonomy. However, field missions require at least to share the output of the sw...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
De Gruyter
2019-12-01
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| Series: | Paladyn |
| Subjects: | |
| Online Access: | https://doi.org/10.1515/pjbr-2019-0033 |
| _version_ | 1797669018607288320 |
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| author | St-Onge David Levillain Florent Zibetti Elisabetta Beltrame Giovanni |
| author_facet | St-Onge David Levillain Florent Zibetti Elisabetta Beltrame Giovanni |
| author_sort | St-Onge David |
| collection | DOAJ |
| description | When faced with the need of implementing a decentralized behavior for a group of collaborating robots, strategies inspired from swarm intelligence often avoid considering the human operator, granting the swarm with full autonomy. However, field missions require at least to share the output of the swarm to the operator. Unfortunately, little is known about the users’ perception of group behavior and dynamics, and there is no clear optimal interaction modality for swarms. In this paper, we focus on the movement of the swarm to convey information to a user: we believe that the interpretation of artificial states based on groups motion can lead to promising natural interaction modalities. We implement a grammar of decentralized control algorithms to explore their expressivity. We define the expressivity of a movement as a metric to measure how natural, readable, or easily understandable it may appear. We then correlate expressivity with the control parameters for the distributed behavior of the swarm. A first user study confirms the relationship between inter-robot distance, temporal and spatial synchronicity, and the perceived expressivity of the robotic system. We follow up with a small group of users tasked with the design of expressive motion sequences to convey internal states using our grammar of algorithms. We comment on their design choices and we assess the interpretation performance by a larger group of users. We show that some of the internal states were perceived as designed and discuss the parameters influencing the performance. |
| first_indexed | 2024-03-11T20:38:04Z |
| format | Article |
| id | doaj.art-2750c487fbcf4ee98f1bb9231f87be68 |
| institution | Directory Open Access Journal |
| issn | 2081-4836 |
| language | English |
| last_indexed | 2024-03-11T20:38:04Z |
| publishDate | 2019-12-01 |
| publisher | De Gruyter |
| record_format | Article |
| series | Paladyn |
| spelling | doaj.art-2750c487fbcf4ee98f1bb9231f87be682023-10-02T04:31:00ZengDe GruyterPaladyn2081-48362019-12-0110141843510.1515/pjbr-2019-0033pjbr-2019-0033Collective expression: how robotic swarms convey information with group motionSt-Onge David0Levillain Florent1Zibetti Elisabetta2Beltrame Giovanni3Department of Mechanical Engineering, École de Technologie Supérieure, Montréal Québec, CanadaEnsadlab-Reflective Interaction, École Nationale Supérieure des Arts Décoratifs, ParisFrance and Costech, Université de Technologie de Compiègne, Compiègne, FranceCHART-LUTIN – EA 4004 Laboratory, Université Paris 8, Saint-Denis – FranceDepartment of Computer and Software Engineering, Polytechnique Montréal, Montréal Québec, CanadaWhen faced with the need of implementing a decentralized behavior for a group of collaborating robots, strategies inspired from swarm intelligence often avoid considering the human operator, granting the swarm with full autonomy. However, field missions require at least to share the output of the swarm to the operator. Unfortunately, little is known about the users’ perception of group behavior and dynamics, and there is no clear optimal interaction modality for swarms. In this paper, we focus on the movement of the swarm to convey information to a user: we believe that the interpretation of artificial states based on groups motion can lead to promising natural interaction modalities. We implement a grammar of decentralized control algorithms to explore their expressivity. We define the expressivity of a movement as a metric to measure how natural, readable, or easily understandable it may appear. We then correlate expressivity with the control parameters for the distributed behavior of the swarm. A first user study confirms the relationship between inter-robot distance, temporal and spatial synchronicity, and the perceived expressivity of the robotic system. We follow up with a small group of users tasked with the design of expressive motion sequences to convey internal states using our grammar of algorithms. We comment on their design choices and we assess the interpretation performance by a larger group of users. We show that some of the internal states were perceived as designed and discuss the parameters influencing the performance.https://doi.org/10.1515/pjbr-2019-0033human-swarm interactionnon-verbal cues and expressivenessevaluation methods and new methodologiesdecentralized controlexpressive motion |
| spellingShingle | St-Onge David Levillain Florent Zibetti Elisabetta Beltrame Giovanni Collective expression: how robotic swarms convey information with group motion Paladyn human-swarm interaction non-verbal cues and expressiveness evaluation methods and new methodologies decentralized control expressive motion |
| title | Collective expression: how robotic swarms convey information with group motion |
| title_full | Collective expression: how robotic swarms convey information with group motion |
| title_fullStr | Collective expression: how robotic swarms convey information with group motion |
| title_full_unstemmed | Collective expression: how robotic swarms convey information with group motion |
| title_short | Collective expression: how robotic swarms convey information with group motion |
| title_sort | collective expression how robotic swarms convey information with group motion |
| topic | human-swarm interaction non-verbal cues and expressiveness evaluation methods and new methodologies decentralized control expressive motion |
| url | https://doi.org/10.1515/pjbr-2019-0033 |
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