Difei Wu, Sheng Zhong, Man Io Leong, Yishun Li, Boyuan Tian, Chenglong Liu, Yuchuan Du
{"title":"考虑轨迹规划和协同操作的路面施工中多碾压机自动化协同方法","authors":"Difei Wu, Sheng Zhong, Man Io Leong, Yishun Li, Boyuan Tian, Chenglong Liu, Yuchuan Du","doi":"10.1111/mice.13347","DOIUrl":null,"url":null,"abstract":"Intelligent compaction, particularly fully autonomous compaction, has emerged as a widely accepted innovative technology for enhancing compaction quality and efficiency. When multiple rollers are concurrently engaged in compaction within the same region, the trajectory planning for each roller and cooperative control become pivotal factors in ensuring efficient and safe compaction. This paper presents a comprehensive methodology framework for achieving safe and efficient cooperative operations in multi-roller automation application. Initially, conventional rollers are retrofitted with autonomous functionality, allowing them to automatically follow preset trajectories through a tracking control algorithm. A trajectory planning method is then proposed, tailored for multi-roller operations. Subsequently, a series of cooperative control strategies are outlined to determine the optimal timing for executing compaction tasks. Additionally, a cooperative control strategy is proposed for multi-roller operations, known as “move forward and backward together” control, which ensures the rollers initiate and cease movement without colliding. Finally, the proposed trajectory planning method and cooperative control strategies are validated through field tests conducted on a 100-m-long, 12-m-wide compaction test site. These tests include single-roller trials, two-roller-in-a-row experiments, and multi-roller cooperation tests. The average trajectory tracking error is maintained below 15 cm, and the effectiveness of the control strategies is demonstrated.","PeriodicalId":156,"journal":{"name":"Computer-Aided Civil and Infrastructure Engineering","volume":"12 1","pages":""},"PeriodicalIF":8.5000,"publicationDate":"2024-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A cooperative methodology for multi-roller automation in pavement construction considering trajectory planning and collaborative operation\",\"authors\":\"Difei Wu, Sheng Zhong, Man Io Leong, Yishun Li, Boyuan Tian, Chenglong Liu, Yuchuan Du\",\"doi\":\"10.1111/mice.13347\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Intelligent compaction, particularly fully autonomous compaction, has emerged as a widely accepted innovative technology for enhancing compaction quality and efficiency. When multiple rollers are concurrently engaged in compaction within the same region, the trajectory planning for each roller and cooperative control become pivotal factors in ensuring efficient and safe compaction. This paper presents a comprehensive methodology framework for achieving safe and efficient cooperative operations in multi-roller automation application. Initially, conventional rollers are retrofitted with autonomous functionality, allowing them to automatically follow preset trajectories through a tracking control algorithm. A trajectory planning method is then proposed, tailored for multi-roller operations. Subsequently, a series of cooperative control strategies are outlined to determine the optimal timing for executing compaction tasks. Additionally, a cooperative control strategy is proposed for multi-roller operations, known as “move forward and backward together” control, which ensures the rollers initiate and cease movement without colliding. Finally, the proposed trajectory planning method and cooperative control strategies are validated through field tests conducted on a 100-m-long, 12-m-wide compaction test site. These tests include single-roller trials, two-roller-in-a-row experiments, and multi-roller cooperation tests. 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A cooperative methodology for multi-roller automation in pavement construction considering trajectory planning and collaborative operation
Intelligent compaction, particularly fully autonomous compaction, has emerged as a widely accepted innovative technology for enhancing compaction quality and efficiency. When multiple rollers are concurrently engaged in compaction within the same region, the trajectory planning for each roller and cooperative control become pivotal factors in ensuring efficient and safe compaction. This paper presents a comprehensive methodology framework for achieving safe and efficient cooperative operations in multi-roller automation application. Initially, conventional rollers are retrofitted with autonomous functionality, allowing them to automatically follow preset trajectories through a tracking control algorithm. A trajectory planning method is then proposed, tailored for multi-roller operations. Subsequently, a series of cooperative control strategies are outlined to determine the optimal timing for executing compaction tasks. Additionally, a cooperative control strategy is proposed for multi-roller operations, known as “move forward and backward together” control, which ensures the rollers initiate and cease movement without colliding. Finally, the proposed trajectory planning method and cooperative control strategies are validated through field tests conducted on a 100-m-long, 12-m-wide compaction test site. These tests include single-roller trials, two-roller-in-a-row experiments, and multi-roller cooperation tests. The average trajectory tracking error is maintained below 15 cm, and the effectiveness of the control strategies is demonstrated.
期刊介绍:
Computer-Aided Civil and Infrastructure Engineering stands as a scholarly, peer-reviewed archival journal, serving as a vital link between advancements in computer technology and civil and infrastructure engineering. The journal serves as a distinctive platform for the publication of original articles, spotlighting novel computational techniques and inventive applications of computers. Specifically, it concentrates on recent progress in computer and information technologies, fostering the development and application of emerging computing paradigms.
Encompassing a broad scope, the journal addresses bridge, construction, environmental, highway, geotechnical, structural, transportation, and water resources engineering. It extends its reach to the management of infrastructure systems, covering domains such as highways, bridges, pavements, airports, and utilities. The journal delves into areas like artificial intelligence, cognitive modeling, concurrent engineering, database management, distributed computing, evolutionary computing, fuzzy logic, genetic algorithms, geometric modeling, internet-based technologies, knowledge discovery and engineering, machine learning, mobile computing, multimedia technologies, networking, neural network computing, optimization and search, parallel processing, robotics, smart structures, software engineering, virtual reality, and visualization techniques.