{"title":"探索任务中机器人群的基于运动的通信","authors":"Corentin Boucher, Rebecca Stower, Vivek Shankar Varadharajan, Elisabetta Zibetti, Florent Levillain, David St-Onge","doi":"10.1007/s10514-022-10079-0","DOIUrl":null,"url":null,"abstract":"<div><p>Many people are fascinated by biological swarms, but understanding the behavior and inherent task objectives of a bird flock or ant colony requires training. Whereas several swarm intelligence works focus on mimicking natural swarm behaviors, we argue that this may not be the most intuitive approach to facilitate communication with the operators. Instead, we focus on the legibility of swarm expressive motions to communicate mission-specific messages to the operator. To do so, we leverage swarm intelligence algorithms on chain formation for resilient exploration and mapping combined with acyclic graph formation (AGF) into a novel swarm-oriented programming strategy. We then explore how expressive motions of robot swarms could be designed and test the legibility of nine different expressive motions in an online user study with 98 participants. We found several differences between the motions in communicating messages to the users. These findings represent a promising starting point for the design of legible expressive motions for implementation in decentralized robot swarms.\n</p></div>","PeriodicalId":55409,"journal":{"name":"Autonomous Robots","volume":null,"pages":null},"PeriodicalIF":3.7000,"publicationDate":"2023-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Motion-based communication for robotic swarms in exploration missions\",\"authors\":\"Corentin Boucher, Rebecca Stower, Vivek Shankar Varadharajan, Elisabetta Zibetti, Florent Levillain, David St-Onge\",\"doi\":\"10.1007/s10514-022-10079-0\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Many people are fascinated by biological swarms, but understanding the behavior and inherent task objectives of a bird flock or ant colony requires training. Whereas several swarm intelligence works focus on mimicking natural swarm behaviors, we argue that this may not be the most intuitive approach to facilitate communication with the operators. Instead, we focus on the legibility of swarm expressive motions to communicate mission-specific messages to the operator. To do so, we leverage swarm intelligence algorithms on chain formation for resilient exploration and mapping combined with acyclic graph formation (AGF) into a novel swarm-oriented programming strategy. We then explore how expressive motions of robot swarms could be designed and test the legibility of nine different expressive motions in an online user study with 98 participants. We found several differences between the motions in communicating messages to the users. These findings represent a promising starting point for the design of legible expressive motions for implementation in decentralized robot swarms.\\n</p></div>\",\"PeriodicalId\":55409,\"journal\":{\"name\":\"Autonomous Robots\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":3.7000,\"publicationDate\":\"2023-01-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Autonomous Robots\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://link.springer.com/article/10.1007/s10514-022-10079-0\",\"RegionNum\":3,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Autonomous Robots","FirstCategoryId":"94","ListUrlMain":"https://link.springer.com/article/10.1007/s10514-022-10079-0","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
Motion-based communication for robotic swarms in exploration missions
Many people are fascinated by biological swarms, but understanding the behavior and inherent task objectives of a bird flock or ant colony requires training. Whereas several swarm intelligence works focus on mimicking natural swarm behaviors, we argue that this may not be the most intuitive approach to facilitate communication with the operators. Instead, we focus on the legibility of swarm expressive motions to communicate mission-specific messages to the operator. To do so, we leverage swarm intelligence algorithms on chain formation for resilient exploration and mapping combined with acyclic graph formation (AGF) into a novel swarm-oriented programming strategy. We then explore how expressive motions of robot swarms could be designed and test the legibility of nine different expressive motions in an online user study with 98 participants. We found several differences between the motions in communicating messages to the users. These findings represent a promising starting point for the design of legible expressive motions for implementation in decentralized robot swarms.
期刊介绍:
Autonomous Robots reports on the theory and applications of robotic systems capable of some degree of self-sufficiency. It features papers that include performance data on actual robots in the real world. Coverage includes: control of autonomous robots · real-time vision · autonomous wheeled and tracked vehicles · legged vehicles · computational architectures for autonomous systems · distributed architectures for learning, control and adaptation · studies of autonomous robot systems · sensor fusion · theory of autonomous systems · terrain mapping and recognition · self-calibration and self-repair for robots · self-reproducing intelligent structures · genetic algorithms as models for robot development.
The focus is on the ability to move and be self-sufficient, not on whether the system is an imitation of biology. Of course, biological models for robotic systems are of major interest to the journal since living systems are prototypes for autonomous behavior.