{"title":"物体运输中异构多变形规划与协调的解耦解决方案","authors":"Weijian Zhang, Charlie Street, Masoumeh Mansouri","doi":"10.1016/j.robot.2024.104773","DOIUrl":null,"url":null,"abstract":"<div><p>Multi-robot formations have numerous applications, such as cooperative object transportation in intelligent warehouses. In this context, robots are tasked with delivering objects in formation while avoiding intra- and inter-formation collisions. This necessitates the development of solutions for multi-robot task allocation, formation generation, rigid formation route planning, and formation coordination. In this paper, we present a cooperative formation object transportation system for heterogeneous multi-robot systems which captures robot dynamics and avoids inter-formation collisions. Accounting for heterogeneous formations expands the applicability of the proposed robotic transport system. For formation generation, we propose an approach based on conflict-based search, which integrates high-level path planning with low-level trajectory optimisation. For heterogeneous formation planning, we present a two-stage iterative trajectory optimisation framework which adheres to the kinematic constraints of our heterogeneous multi-robot system while retaining formation rigidity. For multi-formation coordination, we use a loosely-coupled algorithm which can guarantee collision-free and deadlock-free formation navigation under minimal assumptions. We demonstrate the efficacy of our approach in simulation.</p></div>","PeriodicalId":49592,"journal":{"name":"Robotics and Autonomous Systems","volume":"180 ","pages":"Article 104773"},"PeriodicalIF":4.3000,"publicationDate":"2024-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S092188902400157X/pdfft?md5=e74907924c3b480bce1601e46314e6dc&pid=1-s2.0-S092188902400157X-main.pdf","citationCount":"0","resultStr":"{\"title\":\"A decoupled solution to heterogeneous multi-formation planning and coordination for object transportation\",\"authors\":\"Weijian Zhang, Charlie Street, Masoumeh Mansouri\",\"doi\":\"10.1016/j.robot.2024.104773\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Multi-robot formations have numerous applications, such as cooperative object transportation in intelligent warehouses. In this context, robots are tasked with delivering objects in formation while avoiding intra- and inter-formation collisions. This necessitates the development of solutions for multi-robot task allocation, formation generation, rigid formation route planning, and formation coordination. In this paper, we present a cooperative formation object transportation system for heterogeneous multi-robot systems which captures robot dynamics and avoids inter-formation collisions. Accounting for heterogeneous formations expands the applicability of the proposed robotic transport system. For formation generation, we propose an approach based on conflict-based search, which integrates high-level path planning with low-level trajectory optimisation. For heterogeneous formation planning, we present a two-stage iterative trajectory optimisation framework which adheres to the kinematic constraints of our heterogeneous multi-robot system while retaining formation rigidity. For multi-formation coordination, we use a loosely-coupled algorithm which can guarantee collision-free and deadlock-free formation navigation under minimal assumptions. We demonstrate the efficacy of our approach in simulation.</p></div>\",\"PeriodicalId\":49592,\"journal\":{\"name\":\"Robotics and Autonomous Systems\",\"volume\":\"180 \",\"pages\":\"Article 104773\"},\"PeriodicalIF\":4.3000,\"publicationDate\":\"2024-08-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S092188902400157X/pdfft?md5=e74907924c3b480bce1601e46314e6dc&pid=1-s2.0-S092188902400157X-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Robotics and Autonomous Systems\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S092188902400157X\",\"RegionNum\":2,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"AUTOMATION & CONTROL SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Robotics and Autonomous Systems","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S092188902400157X","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"AUTOMATION & CONTROL SYSTEMS","Score":null,"Total":0}
A decoupled solution to heterogeneous multi-formation planning and coordination for object transportation
Multi-robot formations have numerous applications, such as cooperative object transportation in intelligent warehouses. In this context, robots are tasked with delivering objects in formation while avoiding intra- and inter-formation collisions. This necessitates the development of solutions for multi-robot task allocation, formation generation, rigid formation route planning, and formation coordination. In this paper, we present a cooperative formation object transportation system for heterogeneous multi-robot systems which captures robot dynamics and avoids inter-formation collisions. Accounting for heterogeneous formations expands the applicability of the proposed robotic transport system. For formation generation, we propose an approach based on conflict-based search, which integrates high-level path planning with low-level trajectory optimisation. For heterogeneous formation planning, we present a two-stage iterative trajectory optimisation framework which adheres to the kinematic constraints of our heterogeneous multi-robot system while retaining formation rigidity. For multi-formation coordination, we use a loosely-coupled algorithm which can guarantee collision-free and deadlock-free formation navigation under minimal assumptions. We demonstrate the efficacy of our approach in simulation.
期刊介绍:
Robotics and Autonomous Systems will carry articles describing fundamental developments in the field of robotics, with special emphasis on autonomous systems. An important goal of this journal is to extend the state of the art in both symbolic and sensory based robot control and learning in the context of autonomous systems.
Robotics and Autonomous Systems will carry articles on the theoretical, computational and experimental aspects of autonomous systems, or modules of such systems.