{"title":"基于改进 SSA 算法的移动机器人二维和三维路径规划","authors":"Mailing Zhang, Pei Hao","doi":"10.1007/s41315-024-00374-7","DOIUrl":null,"url":null,"abstract":"<p>In recent years, mobile robots have been widely used in industrial automation, logistics, military, medical, and service industries. However, traditional mobile robots face difficulties in complex path planning. To solve this problem, a robot 2D and 3D path planning method has been proposed. Based on improved sparrow search algorithm (SSA), this method introduces a parameter adaptive update strategy to balance search and development. To enhance the algorithm’s path search capability in 3D environments, this study innovatively introduces ant colony algorithm to generate initial paths based on SSA. It also introduces local search mechanism to help the algorithm select the optimal path. Experiments have shown that the improved algorithm can quickly plan the shortest path, with a length reduction of 3.37% and 6.82%. It has reduced the average length by 6.09% and 5.54%, respectively. To verify its search performance, the improved algorithm significantly improved its convergence accuracy, and improved its mean fitness by about 20.5%, 24%, and 27.5%, respectively. The proposed technology has good application effects and will provide important technical references for mobile robots’ path planning in load environments.</p>","PeriodicalId":44563,"journal":{"name":"International Journal of Intelligent Robotics and Applications","volume":null,"pages":null},"PeriodicalIF":2.1000,"publicationDate":"2024-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"2D and 3D path planning for mobile robots based on improved SSA algorithm\",\"authors\":\"Mailing Zhang, Pei Hao\",\"doi\":\"10.1007/s41315-024-00374-7\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>In recent years, mobile robots have been widely used in industrial automation, logistics, military, medical, and service industries. However, traditional mobile robots face difficulties in complex path planning. To solve this problem, a robot 2D and 3D path planning method has been proposed. Based on improved sparrow search algorithm (SSA), this method introduces a parameter adaptive update strategy to balance search and development. To enhance the algorithm’s path search capability in 3D environments, this study innovatively introduces ant colony algorithm to generate initial paths based on SSA. It also introduces local search mechanism to help the algorithm select the optimal path. Experiments have shown that the improved algorithm can quickly plan the shortest path, with a length reduction of 3.37% and 6.82%. It has reduced the average length by 6.09% and 5.54%, respectively. To verify its search performance, the improved algorithm significantly improved its convergence accuracy, and improved its mean fitness by about 20.5%, 24%, and 27.5%, respectively. The proposed technology has good application effects and will provide important technical references for mobile robots’ path planning in load environments.</p>\",\"PeriodicalId\":44563,\"journal\":{\"name\":\"International Journal of Intelligent Robotics and Applications\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":2.1000,\"publicationDate\":\"2024-08-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Intelligent Robotics and Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1007/s41315-024-00374-7\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ROBOTICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Intelligent Robotics and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1007/s41315-024-00374-7","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ROBOTICS","Score":null,"Total":0}
2D and 3D path planning for mobile robots based on improved SSA algorithm
In recent years, mobile robots have been widely used in industrial automation, logistics, military, medical, and service industries. However, traditional mobile robots face difficulties in complex path planning. To solve this problem, a robot 2D and 3D path planning method has been proposed. Based on improved sparrow search algorithm (SSA), this method introduces a parameter adaptive update strategy to balance search and development. To enhance the algorithm’s path search capability in 3D environments, this study innovatively introduces ant colony algorithm to generate initial paths based on SSA. It also introduces local search mechanism to help the algorithm select the optimal path. Experiments have shown that the improved algorithm can quickly plan the shortest path, with a length reduction of 3.37% and 6.82%. It has reduced the average length by 6.09% and 5.54%, respectively. To verify its search performance, the improved algorithm significantly improved its convergence accuracy, and improved its mean fitness by about 20.5%, 24%, and 27.5%, respectively. The proposed technology has good application effects and will provide important technical references for mobile robots’ path planning in load environments.
期刊介绍:
The International Journal of Intelligent Robotics and Applications (IJIRA) fosters the dissemination of new discoveries and novel technologies that advance developments in robotics and their broad applications. This journal provides a publication and communication platform for all robotics topics, from the theoretical fundamentals and technological advances to various applications including manufacturing, space vehicles, biomedical systems and automobiles, data-storage devices, healthcare systems, home appliances, and intelligent highways. IJIRA welcomes contributions from researchers, professionals and industrial practitioners. It publishes original, high-quality and previously unpublished research papers, brief reports, and critical reviews. Specific areas of interest include, but are not limited to:Advanced actuators and sensorsCollective and social robots Computing, communication and controlDesign, modeling and prototypingHuman and robot interactionMachine learning and intelligenceMobile robots and intelligent autonomous systemsMulti-sensor fusion and perceptionPlanning, navigation and localizationRobot intelligence, learning and linguisticsRobotic vision, recognition and reconstructionBio-mechatronics and roboticsCloud and Swarm roboticsCognitive and neuro roboticsExploration and security roboticsHealthcare, medical and assistive roboticsRobotics for intelligent manufacturingService, social and entertainment roboticsSpace and underwater robotsNovel and emerging applications