{"title":"DDPG-based path planning for cable-driven manipulators in multi-obstacle environments","authors":"Dong Zhang, Renjie Ju, Zhengcai Cao","doi":"10.1017/s0263574724001048","DOIUrl":null,"url":null,"abstract":"<p>Hyper-redundant cable-driven manipulators (CDMs) are widely used for operations in confined spaces due to their slender bodies and multiple degrees of freedom. Most research focuses on their path following but not path planning. This work investigates a deep deterministic policy gradient (DDPG)-based path-planning algorithm for CDMs in multi-obstacle environments. To plan passable paths under many constraints, a DDPG algorithm is modified according to features of CDMs. To improve adaptability of planned paths, a specialized reward function is newly designed. In this function, such factors as smoothness, arrival time and distance are taken into account. Results of simulations and physical experiments are presented to demonstrate the performances of the proposed methods for planning paths of CDMs.</p>","PeriodicalId":49593,"journal":{"name":"Robotica","volume":null,"pages":null},"PeriodicalIF":1.9000,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Robotica","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1017/s0263574724001048","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ROBOTICS","Score":null,"Total":0}
引用次数: 0
Abstract
Hyper-redundant cable-driven manipulators (CDMs) are widely used for operations in confined spaces due to their slender bodies and multiple degrees of freedom. Most research focuses on their path following but not path planning. This work investigates a deep deterministic policy gradient (DDPG)-based path-planning algorithm for CDMs in multi-obstacle environments. To plan passable paths under many constraints, a DDPG algorithm is modified according to features of CDMs. To improve adaptability of planned paths, a specialized reward function is newly designed. In this function, such factors as smoothness, arrival time and distance are taken into account. Results of simulations and physical experiments are presented to demonstrate the performances of the proposed methods for planning paths of CDMs.
期刊介绍：
Robotica is a forum for the multidisciplinary subject of robotics and encourages developments, applications and research in this important field of automation and robotics with regard to industry, health, education and economic and social aspects of relevance. Coverage includes activities in hostile environments, applications in the service and manufacturing industries, biological robotics, dynamics and kinematics involved in robot design and uses, on-line robots, robot task planning, rehabilitation robotics, sensory perception, software in the widest sense, particularly in respect of programming languages and links with CAD/CAM systems, telerobotics and various other areas. In addition, interest is focused on various Artificial Intelligence topics of theoretical and practical interest.
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