{"title":"A local collision-free motion planning strategy for hyper-redundant manipulators based on dynamic safety envelopes","authors":"Renjie Ju, Dong Zhang, Yan Gai, Zhengcai Cao","doi":"10.1017/s0263574724000791","DOIUrl":null,"url":null,"abstract":"Hyper-redundant manipulators (HRMs) exhibit promising adaptability and superior dexterity in cavity detection tasks, owing to their snake-like segmented backbones. Due to the safety concern in contactless operating tasks, reliable motion planning in a confined environment for HRMs is very challenging. However, existing expanding-based obstacle avoidance methods are not feasible in narrow environments, as they will excessively occupy free spaces required for maneuvering. In this work, a local collision-free motion planning strategy based on dynamic safety envelope (DSE) is proposed for HRMs. First, the local motion of HRMs is analyzed in detail, and DSE is proposed for the first time to describe the boundary of the collision-free area. Then, to maximize the efficient utilization of narrow spaces, a reference trajectory for HRM is roughly planned without expanding obstacles. Further, a tip-guided trajectory tracking method based on configuration prediction is proposed by considering the discrete characteristics of rigid links to avoid obstacles. During the tracking process, DSEs are applied to evaluate collision risk and optimize the configuration. Finally, to validate the effectiveness of our proposed method, simulations are conducted, followed by experiments by using a 18-degrees of freedom mobile HRM prototype system.","PeriodicalId":49593,"journal":{"name":"Robotica","volume":null,"pages":null},"PeriodicalIF":1.9000,"publicationDate":"2024-09-12","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/s0263574724000791","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 manipulators (HRMs) exhibit promising adaptability and superior dexterity in cavity detection tasks, owing to their snake-like segmented backbones. Due to the safety concern in contactless operating tasks, reliable motion planning in a confined environment for HRMs is very challenging. However, existing expanding-based obstacle avoidance methods are not feasible in narrow environments, as they will excessively occupy free spaces required for maneuvering. In this work, a local collision-free motion planning strategy based on dynamic safety envelope (DSE) is proposed for HRMs. First, the local motion of HRMs is analyzed in detail, and DSE is proposed for the first time to describe the boundary of the collision-free area. Then, to maximize the efficient utilization of narrow spaces, a reference trajectory for HRM is roughly planned without expanding obstacles. Further, a tip-guided trajectory tracking method based on configuration prediction is proposed by considering the discrete characteristics of rigid links to avoid obstacles. During the tracking process, DSEs are applied to evaluate collision risk and optimize the configuration. Finally, to validate the effectiveness of our proposed method, simulations are conducted, followed by experiments by using a 18-degrees of freedom mobile HRM prototype system.
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.