J. Robotics Mechatronics最新文献_第4页

Consensus Building in Box-Pushing Problem by BRT Agent that Votes with Frequency Proportional to Profit 基于频率与利润成比例投票的BRT代理推箱问题的共识构建

J. Robotics Mechatronics Pub Date : 2023-08-20 DOI: 10.20965/jrm.2023.p1016

M. Kubo, Hiroshi Sato, A. Yamaguchi

引用次数: 0

Special Issue on Design of Swarm Intelligence Through Interdisciplinary Approach 基于跨学科方法的群体智能设计特刊

J. Robotics Mechatronics Pub Date : 2023-08-20 DOI: 10.20965/jrm.2023.p0889

Takeshi Kano, Yuichiro Sueoka

{"title":"Special Issue on Design of Swarm Intelligence Through Interdisciplinary Approach","authors":"Takeshi Kano, Yuichiro Sueoka","doi":"10.20965/jrm.2023.p0889","DOIUrl":"https://doi.org/10.20965/jrm.2023.p0889","url":null,"abstract":"In biological and social systems, a “swarm” refers to a group of individual units that behave as a single intelligent entity. “Swarm behavior,” the collective result of the local interactions among the group members, exhibits what is called “swarm intelligence.” By identifying the design principles of such swarm intelligence, we may be able to create swarm robots that are highly adaptable, fault tolerant, and dimensionally flexible.\u0000 An interdisciplinary approach, including disciplines ranging from technology to biology to the mathematical sciences, for example, is used to elucidate the design principles of swarm intelligence. We believe that such knowledge will lead to transformations in the field of swarm robotics.\u0000 This special issue highlights 19 exciting papers, including 13 research papers, five review papers, and one letter. Some papers focus on understanding the mechanism of real swarm phenomena, while the other papers focus on designing intelligent swarm systems. The keywords of the papers are as follows.\u0000 • Swarm intelligence\u0000 • Interdisciplinary approach\u0000 • Decentralized control\u0000 • Swarm robot\u0000 • Collective behavior\u0000 We would like to express our gratitude to all authors and reviewers, and we hope that this special issue contributes to future research and development in swarm intelligence.","PeriodicalId":178614,"journal":{"name":"J. Robotics Mechatronics","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127601452","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Bi-Connectivity Control for Multi-Robot Network Considering Line-of-Sight Communication 考虑视距通信的多机器人网络双连通性控制

J. Robotics Mechatronics Pub Date : 2023-08-20 DOI: 10.20965/jrm.2023.p1028

T. Murayama, Aoi Iwasaki

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Toward Comparative Collective Behavior to Discover Fundamental Mechanisms Underlying Behavior in Human Crowds and Nonhuman Animal Groups 比较集体行为发现人类群体和非人类动物群体行为的基本机制

J. Robotics Mechatronics Pub Date : 2023-08-20 DOI: 10.20965/jrm.2023.p0922

H. Murakami, M. S. Abe, Y. Nishiyama

{"title":"Toward Comparative Collective Behavior to Discover Fundamental Mechanisms Underlying Behavior in Human Crowds and Nonhuman Animal Groups","authors":"H. Murakami, M. S. Abe, Y. Nishiyama","doi":"10.20965/jrm.2023.p0922","DOIUrl":"https://doi.org/10.20965/jrm.2023.p0922","url":null,"abstract":"This article provides comparative perspectives on collective behaviors that are widely found throughout the animal kingdom, ranging from insect and crustacea swarms, fish schools, bird flocks, and mammal herds to human crowds. Studies of nonhuman animal and human collective behaviors have progressed almost separately even though they have a similar history. Theoretical studies have investigated the reproduction of collective phenomena from simple inter-individual rules, and subsequent empirical and experimental studies have found diverse and complex collective behaviors that are difficult to explain with classical theoretical models. As a consequence, a wide variety of interaction rules have been proposed. To determine models to be implemented in nature and find fundamental mechanisms of collective behaviors, this paper argues that we should compare collective behaviors among various species while adopting Tinbergen’s four questions regarding mechanism, function, development, and evolution as a methodological basis. As an example of a comparative collective behavior paradigm, we introduce our studies in which a mutual anticipation mechanism inspired by nonhuman animal collective behaviors can be linked to a self-organization function in human collective behaviors. We expect that the study of comparative collective behaviors will expand, the methodology will become more sophisticated, and new perspectives regarding the multitemporal features of collective behaviors will emerge.","PeriodicalId":178614,"journal":{"name":"J. Robotics Mechatronics","volume":"67 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122996909","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Effect of Robotic Pile-Up Mechanism on Cooperative Transportation for Versatile Objects 机器人堆垛机构对多用途物体协同运输的影响

J. Robotics Mechatronics Pub Date : 2023-08-20 DOI: 10.20965/jrm.2023.p0938

Yuichiro Sueoka, Wei Jie Yong, Naoto Takebe, Yasuhiro Sugimoto, K. Osuka

引用次数: 0

Cooperative Passing Based on Chaos Theory for Multiple Robot Swarms 基于混沌理论的多机器人群体协同传递

J. Robotics Mechatronics Pub Date : 2023-08-20 DOI: 10.20965/jrm.2023.p0969

Kohei Yamagishi, Tsuyoshi Suzuki

{"title":"Cooperative Passing Based on Chaos Theory for Multiple Robot Swarms","authors":"Kohei Yamagishi, Tsuyoshi Suzuki","doi":"10.20965/jrm.2023.p0969","DOIUrl":"https://doi.org/10.20965/jrm.2023.p0969","url":null,"abstract":"Swarm robotics can cooperatively perform large, multiple tasks by controlling a swarm composed of many robots. Currently, approaches for operating multiple robot swarms are being studied for further evolution of this system. This study addresses a multiple movement task in which robot swarms move collectively in the same environment. In this task, the movement paths of robot swarms must pass each other in a cooperative manner when they intersect. The robots in this system behave under autonomous distributed control, thus must consider a passing behavior suitable for their own situation. This study proposes a turning behavior based on the chaos theory to ensure that a robot swarm avoids other approaching robot swarms. Each robot swarm applying the proposed method passes other swarms while autonomously deciding its turning direction and continuing its own collective movement task. In addition, the decision making based on the chaos theory predicts future values according to the current value. Therefore, it is expected to be useful for task scheduling. The performance of multiple robots passing each other is evaluated with the proposed method using numerical simulations. This performance shows that the robot swarms can avoid each other without collision using the closest inter-robot distance as the evaluation metric. Finally, robot swarms with varying shapes and scales complete their own movements in an environment where these movement paths intersect at a single point.","PeriodicalId":178614,"journal":{"name":"J. Robotics Mechatronics","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117178327","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Group Chase and Escape with Chemotaxis 用化学趋向性组合追逐和逃跑

J. Robotics Mechatronics Pub Date : 2023-08-20 DOI: 10.20965/jrm.2023.p0918

C. Oosawa

引用次数: 0

Evolutionary Design of Cooperative Transport Behavior for a Heterogeneous Robotic Swarm 异构机器人群协同运输行为的进化设计

J. Robotics Mechatronics Pub Date : 2023-08-20 DOI: 10.20965/jrm.2023.p1007

Asad Razzaq, Tomohiro Hayakawa, T. Yasuda

{"title":"Evolutionary Design of Cooperative Transport Behavior for a Heterogeneous Robotic Swarm","authors":"Asad Razzaq, Tomohiro Hayakawa, T. Yasuda","doi":"10.20965/jrm.2023.p1007","DOIUrl":"https://doi.org/10.20965/jrm.2023.p1007","url":null,"abstract":"Swarm robotics system (SRS) is a type of artifact that employs multiple robots to work together in a coordinated way, inspired by the self-organizing behavior of social insects such as ants and bees. SRSs are known for their robustness, flexibility, and scalability. This study focuses on evolutionary robotics (ER) which uses artificial neural networks (ANNs) as controllers to operate autonomous robots. In traditional ER research, SRSs were often composed of teams of homogeneous robots, each of which is controlled by a single ANN. In contrast, this study focuses on the implementation of ER in a heterogeneous SRS. To evaluate our approach, we present the concept of employing multiple controllers for sub-teams in a swarm. Heterogeneity was achieved using different controllers for the same physical bodies. We simulated a cooperative transport task, in which the performance of heterogeneity was superior because the two ANN controllers were able to express a variety of behaviors as an entire swarm. Additionally, this study investigated how well the three types of parental selection methods of the heterogeneous approach, can help to optimize the performance of the swarm.","PeriodicalId":178614,"journal":{"name":"J. Robotics Mechatronics","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126953268","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Biomolecular Motor-Based Swarm Robot: An Innovation in Molecular Delivery 基于生物分子马达的群体机器人:一种分子递送的创新

J. Robotics Mechatronics Pub Date : 2023-08-20 DOI: 10.20965/jrm.2023.p1047

Mousumi Akter, A. Kakugo

引用次数: 0

MBEANN for Robotic Swarm Controller Design and the Behavior Analysis for Cooperative Transport 基于MBEANN的机器人群控制器设计与协同运输行为分析

J. Robotics Mechatronics Pub Date : 2023-08-20 DOI: 10.20965/jrm.2023.p0997

Y. Katada, Takumi Hirokawa, Motoaki Hiraga, K. Ohkura

{"title":"MBEANN for Robotic Swarm Controller Design and the Behavior Analysis for Cooperative Transport","authors":"Y. Katada, Takumi Hirokawa, Motoaki Hiraga, K. Ohkura","doi":"10.20965/jrm.2023.p0997","DOIUrl":"https://doi.org/10.20965/jrm.2023.p0997","url":null,"abstract":"This study focuses on mutation-based evolving artificial neural network (MBEANN), a topology and weight evolving artificial neural network (TWEANN) algorithm. TWEANN optimizes both the connection weights and neural network structure. Primarily, MBEANN uses only mutations to evolve artificial neural networks. An individual in an MBEANN is designed to have a set of sub-networks called operons. Operons are expected to have functions during evolution because they do not recombine with other operons. In this study, we applied MBEANN to design a controller for a robotic swarm on cooperative transport, where the following canonical evolving artificial neural network (EANN) methods do not work well. For comparison with MBEANN, we used an EANN with a fixed network structure and neuroevolution of augmenting topologies (NEAT), which is a widely used TWEANN algorithm. We confirmed that the robot controller that evolved with the MBEANN outperformed the structure-fixed EANN and NEAT controllers. In addition, we investigated the behavior of the swarm robot obtained using the proposed method, in which we deactivated each operon to extract its function. The results show that operons could have their functions, and that several operons could strengthen one another’s functions.","PeriodicalId":178614,"journal":{"name":"J. Robotics Mechatronics","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114876300","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0