{"title":"A real-time collision avoidance method for redundant dual-arm robots in an open operational environment","authors":"Yi Wu , Xiaohui Jia , Tiejun Li , Jinyue Liu","doi":"10.1016/j.rcim.2024.102894","DOIUrl":null,"url":null,"abstract":"<div><div>Due to the structural resemblance of redundant dual-arm robots to human arms, they are widely employed to replace humans in open operational environments. Addressing safety concerns related to the autonomous operations of redundant dual-arm robots in open environments, this paper proposes a real-time collision avoidance method. Firstly, an avoidance direction adjustment algorithm is designed based on the avoidance function method, providing a collision avoidance formulation for the robot control point. Secondly, an obstacle classification algorithm is devised to categorize obstacles into robot body obstacles and end-effector obstacles, and the collision avoidance strategy of redundant dual-arm robots is designed. Subsequently, a collision avoidance penalty factor is introduced based on the proximity between the end-effector and the target point, ensuring the convergence of the joint velocity. Finally, a novel collision avoidance formulation for redundant manipulators is presented, further extended under dual-arm coordinated tasks. Numerical simulations and physical experiments demonstrate that the proposed method can achieve self-collision avoidance for redundant dual-arm robots and dynamic/static obstacle avoidance in dual-arm coordinated tasks, with smooth collision avoidance maneuvers. The research results provide safety guidelines for autonomous operations of redundant dual-arm robots in open operational environments.</div></div>","PeriodicalId":21452,"journal":{"name":"Robotics and Computer-integrated Manufacturing","volume":"92 ","pages":"Article 102894"},"PeriodicalIF":9.1000,"publicationDate":"2024-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Robotics and Computer-integrated Manufacturing","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0736584524001819","RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 0
Abstract
Due to the structural resemblance of redundant dual-arm robots to human arms, they are widely employed to replace humans in open operational environments. Addressing safety concerns related to the autonomous operations of redundant dual-arm robots in open environments, this paper proposes a real-time collision avoidance method. Firstly, an avoidance direction adjustment algorithm is designed based on the avoidance function method, providing a collision avoidance formulation for the robot control point. Secondly, an obstacle classification algorithm is devised to categorize obstacles into robot body obstacles and end-effector obstacles, and the collision avoidance strategy of redundant dual-arm robots is designed. Subsequently, a collision avoidance penalty factor is introduced based on the proximity between the end-effector and the target point, ensuring the convergence of the joint velocity. Finally, a novel collision avoidance formulation for redundant manipulators is presented, further extended under dual-arm coordinated tasks. Numerical simulations and physical experiments demonstrate that the proposed method can achieve self-collision avoidance for redundant dual-arm robots and dynamic/static obstacle avoidance in dual-arm coordinated tasks, with smooth collision avoidance maneuvers. The research results provide safety guidelines for autonomous operations of redundant dual-arm robots in open operational environments.
期刊介绍:
The journal, Robotics and Computer-Integrated Manufacturing, focuses on sharing research applications that contribute to the development of new or enhanced robotics, manufacturing technologies, and innovative manufacturing strategies that are relevant to industry. Papers that combine theory and experimental validation are preferred, while review papers on current robotics and manufacturing issues are also considered. However, papers on traditional machining processes, modeling and simulation, supply chain management, and resource optimization are generally not within the scope of the journal, as there are more appropriate journals for these topics. Similarly, papers that are overly theoretical or mathematical will be directed to other suitable journals. The journal welcomes original papers in areas such as industrial robotics, human-robot collaboration in manufacturing, cloud-based manufacturing, cyber-physical production systems, big data analytics in manufacturing, smart mechatronics, machine learning, adaptive and sustainable manufacturing, and other fields involving unique manufacturing technologies.